Metop First Generation AVHRR FRAC SST Reanalysis Version 1

The first full-mission global AVHRR FRAC sea surface temperature (SST) dataset with a nominal 1.1km resolution at nadir was produced from three Metop First Generation (FG) satellites: Metop-A (2006-on), -B (2012-on) and -C (2018-on), using the NOAA Advanced Clear Sky Processor for Ocean (ACSPO) SST enterprise system. Historical reprocessing (‘Reanalysis-1’, RAN1) starts at the beginning of each mission and continues into near-real time (NRT). ACSPO generates two SST products, one with global regression (GR; highly sensitive to skin SST), and another one with piecewise regression (PWR; proxy for depth SST) algorithms. Small residual effects of orbital and sensor instabilities on SST retrievals are mitigated by retraining the regression coefficients daily, using matchups with drifting and tropical moored buoys within moving time windows. In RAN, the training windows are centered at the processed day. In NRT, the same size windows are employed but delayed in time, ending four to ten days prior to the processed day. Delayed-mode RAN reprocessing follows the NRT with a two-month lag, resulting in a higher quality and a more consistent SST record. In addition to its completeness, the newly created Metop-FG RAN1 SST dataset shows very close agreement with in situ data (including the fully independent Argo floats), well within the NOAA specifications for accuracy (global mean bias; ±0.2 K) and precision (global standard deviation; 0.6 K) in a ~20% clear-sky domain (percent of clear-sky SST pixels to the total of ice-free ocean). All performance statistics are stable in time, and consistent across the three platforms. The Metop-FG RAN1 data set is archived at the NASA JPL PO.DAAC and NOAA NCEI. This paper documents the newly created dataset and evaluates its performance.

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Sensor-Specific Error Statistics for SST in the Advanced Clear-Sky Processor for Oceans

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-15-0166.1 ◽

2016 ◽

Vol 33 (2) ◽

pp. 345-359 ◽

Cited By ~ 10

Author(s):

B. Petrenko ◽

A. Ignatov ◽

Y. Kihai ◽

P. Dash

Keyword(s):

Regression Coefficients ◽

Local Regression ◽

Error Statistics ◽

Surface Warming ◽

Piecewise Regression ◽

Clear Sky ◽

In Situ Data ◽

Fitting In ◽

Specific Error

AbstractThe formulation of the sensor-specific error statistics (SSES) has been redesigned in the latest implementation of the NOAA Advanced Clear-Sky Processor for Oceans (ACSPO) to enable efficient use of SSES for assimilation of the ACSPO baseline regression SST (BSST) into level 4 (L4) analyses. The SSES algorithm employs segmentation of the SST domain in the space of regressors and derives the segmentation parameter from the statistics of regressors within the global dataset of matchups. For each segment, local regression coefficients and standard deviations (SDs) of BSST minus in situ SST are calculated from the corresponding subset of matchups. The local regression coefficients are used to generate an auxiliary product—piecewise regression (PWR) SST—and SSES biases are estimated as differences between BSST and PWR SST. Correction of SSES biases, which transforms BSST back into PWR SST, reduces the effects of residual cloud; variations in view zenith angle; and, during the daytime, diurnal surface warming. This results in significant reduction in the global SD of fitting in situ SST, making it comparable with SD for the Canadian Meteorological Centre (CMC) L4 SST. Unlike the foundation CMC SST (which is consistent with in situ SST at night but biased cold during the daytime), the PWR SST is consistent with in situ data during both day and night and thus may be viewed as an estimate of “depth” in situ SST. The PWR SST is expected to be a useful input into L4 SST analyses, especially for foundation SST products, such as the CMC L4.

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Complex networks of earthquakes and aftershocks

Nonlinear Processes in Geophysics ◽

10.5194/npg-12-1-2005 ◽

2005 ◽

Vol 12 (1) ◽

pp. 1-11 ◽

Cited By ~ 56

Author(s):

M. Baiesi ◽

M. Paczuski

Keyword(s):

Complex Networks ◽

Time Windows ◽

Scaling Law ◽

Relative Strength ◽

Modern Theory ◽

Significant Information ◽

Data Set ◽

Scale Free ◽

Main Shocks ◽

Aftershock Sequences

Abstract. We invoke a metric to quantify the correlation between any two earthquakes. This provides a simple and straightforward alternative to using space-time windows to detect aftershock sequences and obviates the need to distinguish main shocks from aftershocks. Directed networks of earthquakes are constructed by placing a link, directed from the past to the future, between pairs of events that are strongly correlated. Each link has a weight giving the relative strength of correlation such that the sum over the incoming links to any node equals unity for aftershocks, or zero if the event had no correlated predecessors. A correlation threshold is set to drastically reduce the size of the data set without losing significant information. Events can be aftershocks of many previous events, and also generate many aftershocks. The probability distribution for the number of incoming and outgoing links are both scale free, and the networks are highly clustered. The Omori law holds for aftershock rates up to a decorrelation time that scales with the magnitude, m, of the initiating shock as tcutoff~10β m with β~-3/4. Another scaling law relates distances between earthquakes and their aftershocks to the magnitude of the initiating shock. Our results are inconsistent with the hypothesis of finite aftershock zones. We also find evidence that seismicity is dominantly triggered by small earthquakes. Our approach, using concepts from the modern theory of complex networks, together with a metric to estimate correlations, opens up new avenues of research, as well as new tools to understand seismicity.

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The Effect of Moist Convection on the Tropospheric Response to Tropical and Subtropical Zonally Asymmetric Torques

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-13-041.1 ◽

2013 ◽

Vol 70 (12) ◽

pp. 4089-4111 ◽

Cited By ~ 5

Author(s):

William R. Boos ◽

Tiffany A. Shaw

Keyword(s):

Vertical Motion ◽

Static Stability ◽

Moist Convection ◽

Motion Response ◽

Clear Sky ◽

Double Itcz ◽

Highly Sensitive ◽

Equatorial Wave ◽

Meridional Overturning ◽

Basic States

Abstract Tropospheric winds can be altered by vertical transfers of momentum due to orographic gravity waves and convection. Previous work showed that, in dry models, such zonally asymmetric torques produce a pattern of tropical ascent that is well described by linear dynamics, together with meridional shifts of the midlatitude jet. Here a series of idealized models is used to understand the effects of moisture on the tropospheric response to tropical and subtropical zonally asymmetric, upper-tropospheric torques. The vertical motion response to a torque is shown to be amplified by the reduction in effective static stability that occurs in moist convecting atmospheres. This amplification occurs only in precipitating regions, and the magnitude of subsidence in nonprecipitating regions saturates when clear-sky radiative cooling balances induced adiabatic warming. For basic states in which precipitation is concentrated in an intertropical convergence zone (ITCZ), most of the vertical motion response is thus confined within the basic-state ITCZ, even when the torque is remote from the ITCZ. Tropical and subtropical torques perturb the extratropical baroclinic eddy field and the convectively coupled equatorial wave field. Resulting changes in momentum flux convergence by transient eddies induce secondary meridional overturning circulations that modify the zonal-mean response to a torque. The net effect allows tropical torques to merge a double ITCZ into a single equatorial ITCZ. The response of tropical transient eddies is highly sensitive to the representation of convection, so the zonal-mean response to a torque is similarly sensitive, even when the torque is located in the subtropics.

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Time Windows Voting Classifier for COVID-19 Mortality Prediction

10.1101/2021.07.02.21259934 ◽

2021 ◽

Author(s):

TIONG GOH ◽

MengJun Liu

Keyword(s):

Time Window ◽

Majority Vote ◽

Time Windows ◽

Mortality Prediction ◽

Data Set ◽

Risk Of Mortality ◽

Machine Learning Model ◽

Partitioned Data ◽

Considerable Impact ◽

Extended Duration

The ability to predict COVID-19 patients' level of severity (death or survival) enables clinicians to prioritise treatment. Recently, using three blood biomarkers, an interpretable machine learning model was developed to predict the mortality of COVID-19 patients. The method was reported to be suffering from performance stability because the identified biomarkers are not consistent predictors over an extended duration. To sustain performance, the proposed method partitioned data into three different time windows. For each window, an end-classifier, a mid-classifier and a front-classifier were designed respectively using the XGboost single tree approach. These time window classifiers were integrated into a majority vote classifier and tested with an isolated test data set. The voting classifier strengthens the overall performance of 90% cumulative accuracy from a 14 days window to a 21 days prediction window. An additional 7 days of prediction window can have a considerable impact on a patient's chance of survival. This study validated the feasibility of the time window voting classifier and further support the selection of biomarkers features set for the early prognosis of patients with a higher risk of mortality.

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MODIS observed increase in duration and spatial extent of sediment plumes in Greenland fjords

The Cryosphere ◽

10.5194/tc-8-1161-2014 ◽

2014 ◽

Vol 8 (4) ◽

pp. 1161-1176 ◽

Cited By ~ 30

Author(s):

B. Hudson ◽

I. Overeem ◽

D. McGrath ◽

J. P. M. Syvitski ◽

A. Mikkelsen ◽

...

Keyword(s):

North Atlantic Ocean ◽

Regional Scale ◽

Greenland Ice Sheet ◽

Sediment Concentration ◽

Retrieval Algorithm ◽

Freshwater Flux ◽

River Plumes ◽

Data Set ◽

In Situ Data ◽

The North

Abstract. The freshwater flux from the Greenland Ice Sheet (GrIS) to the North Atlantic Ocean carries extensive but poorly documented volumes of sediment. We develop a suspended sediment concentration (SSC) retrieval algorithm using a large Greenland specific in situ data set. This algorithm is applied to all cloud-free NASA Moderate Resolution Imaging Spectrometer (MODIS) Terra images from 2000 to 2012 to monitor SSC dynamics at six river plumes in three fjords in southwest Greenland. Melt-season mean plume SSC increased at all but one site, although these trends were primarily not statistically significant. Zones of sediment concentration > 50 mg L−1 expanded in three river plumes, with potential consequences for biological productivity. The high SSC cores of sediment plumes ( > 250 mg L−1 expanded in one-third of study locations. At a regional scale, higher volumes of runoff were associated with higher melt-season mean plume SSC values, but this relationship did not hold for individual rivers. High spatial variability between proximal plumes highlights the complex processes operating in Greenland's glacio–fluvial–fjord systems.

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Reassessing the Generational Disparity in Immigrant Offending: A Within-family Comparison of Involvement in Crime

Journal of Research in Crime and Delinquency ◽

10.1177/0022427819850600 ◽

2019 ◽

Vol 56 (6) ◽

pp. 851-887 ◽

Cited By ~ 2

Author(s):

Bianca E. Bersani ◽

Adam W. Pittman

Keyword(s):

First Generation ◽

Second Generation ◽

Well Being ◽

Foreign Born ◽

Data Set ◽

The Difference ◽

Successive Generations ◽

Offending Patterns ◽

High Degree ◽

Parent Child

Objective:This study reassesses the generational disparity in immigrant offending. Patterns and predictors of offending are compared using traditional peer-based models and an alternative within-family (parent–child dyad) model.Method:The National Longitudinal Survey of Youth (1979; NLSY79) and NLSY-Child and Young Adult (NLSY_CYA) data are merged to create an intergenerational data set to compare generational disparities in immigrant offending across peers and within families. Differences in self-reported offending (prevalence and variety) by immigrant generation are assessed using a combination of descriptive analyses (χ2and analysis of variance) and regression models.Results:While NLSY_CYA children generally are at a greater risk of offending compared with the NLSY79 mothers, the difference in offending is greatest between first-generation mom and second-generation child dyads. Disparities in offending are driven in large part by exceedingly low levels of offending among first-generation immigrants.Conclusion:Although the factors driving an increase in offending between parent–child generations are not unique to immigrants, they are amplified in immigrant families. Whereas the second generation is remarkably similar to their U.S.-born counterparts in terms of their involvement in crime, suggesting a high degree of swift integration, the greater involvement in crime among the children of immigrants compared to their foreign-born mothers suggests a decline in well-being across successive generations.

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Four steps to standardize reporting of peritoneal dialysis technique failure: A proposed approach

Peritoneal Dialysis International ◽

10.1177/0896860820976935 ◽

2020 ◽

pp. 089686082097693

Author(s):

Alix Clarke ◽

Pietro Ravani ◽

Matthew J Oliver ◽

Mohamed Mahsin ◽

Ngan N Lam ◽

...

Keyword(s):

Peritoneal Dialysis ◽

Outcome Measure ◽

Time Window ◽

Time Windows ◽

Dialysis Patients ◽

Data Set ◽

The Impact ◽

Technique Failure ◽

Standardize Reporting ◽

Dialysis Technique

Background: Technique failure is an important outcome measure in research and quality improvement in peritoneal dialysis (PD) programs, but there is a lack of consistency in how it is reported. Methods: We used data collected about incident dialysis patients from 10 Canadian dialysis programs between 1 January 2004 and 31 December 2018. We identified four main steps that are required when calculating the risk of technique failure. We changed one variable at a time, and then all steps, simultaneously, to determine the impact on the observed risk of technique failure at 24 months. Results: A total of 1448 patients received PD. Selecting different cohorts of PD patients changed the observed risk of technique failure at 24 months by 2%. More than one-third of patients who switched to hemodialysis returned to PD—90% returned within 180 days. The use of different time windows of observation for a return to PD resulted in risks of technique failure that differed by 16%. The way in which exit events were handled during the time window impacted the risk of technique failure by 4% and choice of statistical method changed results by 4%. Overall, the observed risk of technique failure at 24 months differed by 20%, simply by applying different approaches to the same data set. Conclusions: The approach to reporting technique failure has an important impact on the observed results. We present a robust and transparent methodology to track technique failure over time and to compare performance between programs.

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Comparison of MODIS 3 km and 10 km resolution aerosol optical depth retrievals over land with airborne sunphotometer measurements during ARCTAS summer 2008

Atmospheric Chemistry and Physics ◽

10.5194/acp-14-2015-2014 ◽

2014 ◽

Vol 14 (4) ◽

pp. 2015-2038 ◽

Cited By ~ 26

Author(s):

J. M. Livingston ◽

J. Redemann ◽

Y. Shinozuka ◽

R. Johnson ◽

P. B. Russell ◽

...

Keyword(s):

Aerosol Optical Depth ◽

Optical Depth ◽

Retrieval Algorithm ◽

Grid Cells ◽

Data Set ◽

Clear Sky ◽

Modis Aod ◽

Research Aircraft ◽

Bright Surface ◽

Moderate Resolution Imaging Spectroradiometer

Abstract. Airborne sunphotometer measurements acquired by the NASA Ames Airborne Tracking Sunphotometer (AATS-14) aboard the NASA P-3 research aircraft are used to evaluate dark-target over-land retrievals of extinction aerosol optical depth (AOD) from spatially and temporally near-coincident measurements by the Moderate Resolution Imaging Spectroradiometer (MODIS) during the summer 2008 Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) field campaign. The new MODIS Collection 6 aerosol data set includes retrievals of AOD at both 10 km × 10 km and 3 km × 3 km (at nadir) resolution. In this paper we compare MODIS and AATS AOD at 553 nm in 58 10 km and 134 3 km retrieval grid cells. These AOD values were derived from data collected over Canada on four days during short time segments of five (four Aqua and one Terra) satellite overpasses of the P-3 during low-altitude P-3 flight tracks. Three of the five MODIS–AATS coincidence events were dominated by smoke: one included a P-3 transect of a well-defined smoke plume in clear sky, but two were confounded by the presence of scattered clouds above smoke. The clouds limited the number of MODIS retrievals available for comparison, and led to MODIS AOD retrievals that underestimated the corresponding AATS values. This happened because the MODIS aerosol cloud mask selectively removed 0.5 km pixels containing smoke and clouds before the aerosol retrieval. The other two coincidences (one Terra and one Aqua) occurred during one P-3 flight on the same day and in the same general area, in an atmosphere characterized by a relatively low AOD (< 0.3), spatially homogeneous regional haze from smoke outflow with no distinguishable plume. For the ensemble data set for MODIS AOD retrievals with the highest-quality flag, MODIS AOD agrees with AATS AOD within the expected MODIS over-land AOD uncertainty in 60% of the retrieval grid cells at 10 km resolution and 69% at 3 km resolution. These values improve to 65 % and 74%, respectively, when the cloud-affected case with the strongest plume is excluded. We find that the standard MODIS dark-target over-land retrieval algorithm fails to retrieve AOD for thick smoke, not only in cloud-contaminated regions but also in clear sky. We attribute this to deselection, by the cloud and/or bright surface masks, of 0.5 km resolution pixels that contain smoke.

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Interpretation of reflection attributes in a 3-D GPR survey at Vallée d’Ossau, western Pyrenees, France

Geophysics ◽

10.1190/1.1444832 ◽

2000 ◽

Vol 65 (5) ◽

pp. 1435-1445 ◽

Cited By ~ 24

Author(s):

Pascale Sénéchal ◽

Hervé Perroud ◽

Guy Sénéchal

Keyword(s):

Water Saturation ◽

Time Windows ◽

Amplitude Analysis ◽

Glacial Deposits ◽

Data Set ◽

Limestone Bedrock ◽

Strong Amplitude ◽

Karstic Limestone ◽

Water Saturated ◽

Western Pyrenees

To study the attributes of reflected radar waves, a 3-D ground‐penetrating radar (GPR) data set was recorded, processed with ProMAX 3-D seismic processing software, and analyzed with Stratimagic 3-D seismic interpretation software. The zone studied was an old glacial valley (Vallée d’Ossau, western Pyrenees) where fluvio‐glacial deposits (8–10 m thick) overlay a karstic limestone bedrock. Reflections were picked to 250 ns (9 m depth with velocity υ = 0.07 m/ns). Analysis of the isochron map of the bedrock surface reflector showed north‐south undulations, corresponding to the displacement of the old glacier, together with sharp discontinuities, interpreted as local faults or karstic zones. Amplitude variations along the reflector were interpreted as being from water saturation and the nearby north‐south alignment of springs at the surface. In the fluvio‐glacial deposits, paths of old channels were also imaged using amplitude analysis. The radar‐wave amplitude attenuation was also characterized within the deposits by analyzing the average absolute amplitude for different time windows. The strong amplitude attenuations were interpreted as the result of water‐saturated zones. As a conclusion, we correlated the surface karstic springs with bedrock structures and followed the water path across the glacial sedimentary filling. The recognized features were very consistent with a 2-D dc resistivity profile made through the GPR data block.

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Evaluation of the MOZAIC Capacitive Hygrometer during the airborne field study CIRRUS-III

Atmospheric Measurement Techniques ◽

10.5194/amt-8-1233-2015 ◽

2015 ◽

Vol 8 (3) ◽

pp. 1233-1243 ◽

Cited By ~ 7

Author(s):

P. Neis ◽

H. G. J. Smit ◽

M. Krämer ◽

N. Spelten ◽

A. Petzold

Keyword(s):

Ambient Temperature ◽

Field Study ◽

Laser System ◽

Distribution Functions ◽

Tunable Diode Laser ◽

Data Set ◽

Clear Sky ◽

Operation Conditions ◽

Open Path ◽

Passenger Aircraft

Abstract. The MOZAIC Capacitive Hygrometer (MCH) is usually operated aboard passenger aircraft in the framework of MOZAIC (Measurement of Ozone by Airbus In-Service Aircraft) for measuring atmospheric relative humidity (RH). In order to evaluate the performance of the MCH, the instrument was operated aboard a Learjet 35A research aircraft as part of the CIRRUS-III field study together with a closed-cell Lyman-α fluorescence hygrometer (Fast in situ Stratospheric Hygrometer, or FISH) and an open-path tunable diode laser system (Open-path Jülich Stratospheric TDL ExpeRiment, or OJSTER) for water vapour measurement. After reducing the CIRRUS-III data set to data corresponding to MOZAIC aircraft operation conditions, the 1 Hz RH data cross correlation between the MCH and reference instruments FISH (clear sky) and OJSTER (in-cirrus) yielded a remarkably good agreement of R2 = 0.92 and slope m = 1.02 and provided a MCH uncertainty of 5% RH. Probability distribution functions of RH deduced from the MCH and reference instruments agreed well between 10 and 70% RH with respect to liquid water in the ambient temperature range of ca. −70 to −40 °C. The use of MCH data is limited to sensor temperatures above the calibration limit of Tsensor = −40 °C (corresponds to ambient temperature of Tambient = −70 °C at typical cruising speed of long-haul passenger aircraft). Good performance of the MCH for clear sky as well as for in-cirrus conditions demonstrated the sensor robustness also for operation inside ice clouds.

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