Model Identification for Estimating Missing Values in Space-Time Data Series: Monthly Inflation in the US Urban System, 1977–1990

The Local Consumer Commerce Index is a measure of local economic activity parsed by a variety of consumer and merchant characteristics. By leveraging an administrative database of over 24 billion debit and credit card transactions made by over 64 million de-identified customers, this index from the JPMorgan Chase Institute addresses the lack of data series with sufficient spatiotemporal and demo/firmographic resolution to support tactical decision making in local economies. Each transaction carries the age and income of the consumer, the merchant size and type of product it sells, as well as the zip code of both. Using these characteristics we construct a measure of year-over-year spending growth by consumers at merchants located in 14 major metropolitan areas in the US. The index data are screened and weighted to represent population-wide spending levels. This unique lens on local economies is freely provided to the public in accordance with the Institute’s mission of advancing the public good. We have also extended this data asset beyond its use for reporting and economic monitoring. One extension has been our research that measures intra-city demand. By measuring the distance between where consumers live and the merchants at which they shop, we have lent nuance and granularity to policy discussions surrounding intra-city inequities in economic vitality. We hope to socialize the power of leveraging administrative data for the public good, in hopes that other administrative data-owners are encouraged to also furnish analyses based on their administrative data to help inform the public policy process.

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Space Time Data Analysis for Greenhouse Whitefly

Korean Journal of Applied Statistics ◽

10.5351/kjas.2004.17.3.403 ◽

2004 ◽

Vol 17 (3) ◽

pp. 403-418

Keyword(s):

Data Analysis ◽

Space Time ◽

Time Data ◽

Greenhouse Whitefly

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Noise performance of microwave humidity sounders over their life time

10.5194/amt-2017-277 ◽

2017 ◽

Author(s):

Imke Hans ◽

Martin Burgdorf ◽

Viju O. John ◽

Jonathan Mittaz ◽

Stefan A. Buehler

Keyword(s):

Uncertainty Propagation ◽

Life Time ◽

Noise Spectrum ◽

Data Series ◽

Allan Deviation ◽

Noise Performance ◽

Climate Data ◽

Time Data ◽

Accessible Information ◽

Long Time

Abstract. The microwave humidity sounders Special Sensor Microwave Water Vapour Profiler (SSMT-2), Advanced Microwave Sounding Unit-B (AMSU-B) and Microwave Humidity Sounder (MHS) to date have been providing data records for 25 years. So far, the data records lack uncertainty information essential for constructing consistent long time data series. In this study, we assess the quality of the recorded data with respect to the uncertainty caused by noise. We calculate the noise on the raw calibration counts from the deep space view (DSV) of the instrument and the Noise Equivalent Differential Temperature (NEΔT) as a measure for the radiometer sensitivity. For this purpose, we use the Allan Deviation that is not biased from an underlying varying mean of the data and that has been suggested only recently for application in atmospheric remote sensing. Moreover, we use the bias function related to the Allan Deviation to infer the underlying spectrum of the noise. As examples, we investigate the noise spectrum in flight for some instruments. For the assessment of the noise evolution in time, we provide a descriptive and graphical overview of the calculated NEΔT over the life span of each instrument and channel. This overview can serve as an easily accessible information for users interested in the noise performance of a specific instrument, channel and time. Within the time evolution of the noise, we identify periods of instrumental degradation, which manifest themselves in an increasing NEΔT, and periods of erratic behaviour, which show sudden increases of NEΔT interrupting the overall smooth evolution of the noise. From this assessment and subsequent exclusion of the aforementioned periods, we present a chart showing available data records with NEΔT < K. Due to overlapping life spans of the instruments, these reduced data records still cover without gaps the time since 1994 and may therefore serve as first step for constructing long time series. Our method for count noise estimation, that has been used in this study, will be used in the data processing to provide input values for the uncertainty propagation in the generation of a new set of Fundamental Climate Data Records (FCDR) that are currently produced in the project Fidelity and Uncertainty in Climate data records from Earth Observation (FIDUCEO).

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