Constructing a long-term monthly climate data set in central Asia

Abstract A moisture reference year (MRY) is generally used to assess the durability, or long-term performance of building envelopes within a long climatological time period, e.g. a 31 year timeframe. The intent of this paper is to develop a set of moisture reference years that can be used to assess risk to the formation of mould growth in wood-frame buildings over the long-term. The set of moisture reference years have been developed based on 15 realizations of 31-year climate data. Replicated Latin Hypercube Sampling is applied to select 15 sub-realizations with 7 representative years having different levels of moisture index (MI) from each realization. Thereafter, hygrothermal simulations are performed for a brick veneer clad wood-frame wall assembly using the 15 sub-realizations; that sub-realization which produces the highest value of maximum mould growth index over 7-year period is selected as the MRY. The selection process is then implemented for all 15 realizations of the 31-years of data sets, from which 15 sets of 7-year long MRYs are selected to represent the original 15 realizations. It is shown that the 15 sets of 7-year long MRYs can produce the same value of maximum mould growth index as well as the uncertainty as compared to the original 15 realizations having a 31-year climate data set.

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How long do satellites need to overlap? Evaluation of climate data stability from overlapping satellite records

Atmospheric Chemistry and Physics ◽

10.5194/acp-17-15069-2017 ◽

2017 ◽

Vol 17 (24) ◽

pp. 15069-15093 ◽

Cited By ~ 6

Author(s):

Elizabeth C. Weatherhead ◽

Jerald Harder ◽

Eduardo A. Araujo-Pradere ◽

Greg Bodeker ◽

Jason M. English ◽

...

Keyword(s):

Solar Radiation ◽

Spectral Irradiance ◽

Data Sets ◽

Climate Data ◽

Data Set ◽

Long Term Stability ◽

Earth Observations ◽

Earth’S Climate ◽

The Stability

Abstract. Sensors on satellites provide unprecedented understanding of the Earth's climate system by measuring incoming solar radiation, as well as both passive and active observations of the entire Earth with outstanding spatial and temporal coverage. A common challenge with satellite observations is to quantify their ability to provide well-calibrated, long-term, stable records of the parameters they measure. Ground-based intercomparisons offer some insight, while reference observations and internal calibrations give further assistance for understanding long-term stability. A valuable tool for evaluating and developing long-term records from satellites is the examination of data from overlapping satellite missions. This paper addresses how the length of overlap affects the ability to identify an offset or a drift in the overlap of data between two sensors. Ozone and temperature data sets are used as examples showing that overlap data can differ by latitude and can change over time. New results are presented for the general case of sensor overlap by using Solar Radiation and Climate Experiment (SORCE) Spectral Irradiance Monitor (SIM) and Solar Stellar Irradiance Comparison Experiment (SOLSTICE) solar irradiance data as an example. To achieve a 1 % uncertainty in estimating the offset for these two instruments' measurement of the Mg II core (280 nm) requires approximately 5 months of overlap. For relative drift to be identified within 0.1 % yr−1 uncertainty (0.00008 W m−2 nm−1 yr−1), the overlap for these two satellites would need to be 2.5 years. Additional overlap of satellite measurements is needed if, as is the case for solar monitoring, unexpected jumps occur adding uncertainty to both offsets and drifts; the additional length of time needed to account for a single jump in the overlap data may be as large as 50 % of the original overlap period in order to achieve the same desired confidence in the stability of the merged data set. Results presented here are directly applicable to satellite Earth observations. Approaches for Earth observations offer additional challenges due to the complexity of the observations, but Earth observations may also benefit from ancillary observations taken from ground-based and in situ sources. Difficult choices need to be made when monitoring approaches are considered; we outline some attempts at optimizing networks based on economic principles. The careful evaluation of monitoring overlap is important to the appropriate application of observational resources and to the usefulness of current and future observations.

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Twentieth-century variations in temperature and precipitation in the Nordic Arctic

Polar Record ◽

10.1017/s0032247400017721 ◽

2002 ◽

Vol 38 (206) ◽

pp. 203-210 ◽

Cited By ~ 20

Author(s):

E. J. Førland ◽

I. Hanssen-Bauer ◽

T. Jónsson ◽

C. Kern-Hansen ◽

P.Ø. Nordli ◽

...

Keyword(s):

Twentieth Century ◽

Temperature Trend ◽

Annual Precipitation ◽

Data Series ◽

Positive Trend ◽

Positive Temperature ◽

Climate Data ◽

Data Set ◽

Temperature And Precipitation

AbstractIn a joint Nordic effort, a high-quality climate data set for the Nordic Arctic is established. The data set consists of monthly values from 20 stations in Greenland, Iceland, the Faeroes, and the Norwegian Arctic. The data set is made available on the web. Ten climate elements are included, and most of the series covers the period 1890–2000. The data series illustrate the large climatic contrasts in the Nordic Arctic, and demonstrate that parts of the region have experienced substantial climate variations during the last century. Despite increasing temperatures during recent decades, the present temperature level is still lower than in the 1930s and 1950s in large parts of the region. The pattern of long-term precipitation variations is more complicated, but in parts of the region the annual precipitation has increased substantially. At Svalbard Airport and Bjørnøya the annual precipitation has increased by more than 2.5% per decade during the twentieth century.Variations in atmospheric circulation can account for most of the long-term positive trend in precipitation in the Norwegian Arctic, and also for the positive temperature trend from the 1960s. The positive temperature trend before 1930 and the negative trend during the following decades, are, however, not accounted for by the circulation models.

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Developing a Dust Emission Procedure for Central Asia

Air Soil and Water Research ◽

10.1177/1178622117711939 ◽

2017 ◽

Vol 10 ◽

pp. 117862211771193 ◽

Cited By ~ 5

Author(s):

Longlei Li ◽

Irina N Sokolik

Keyword(s):

Central Asia ◽

Regional Climate ◽

Land Use Changes ◽

Dust Emission ◽

Recent Decade ◽

Weather Research And Forecasting ◽

Data Set ◽

Source Regions ◽

Microphysical Processes

Airborne mineral dust is thought to have a significant influence on the climate through absorbing and scattering both shortwave and longwave radiations and affecting cloud microphysical processes. However, a knowledge of long-term dust emissions is limited from both temporal and spatial perspectives. Here, we have developed a quantitative climatology: the column-integrated mass of the dust aerosol loading in Central Asia by incorporating the dust module (DuMo) into the Weather Research and Forecasting coupled with Chemistry (WRF-Chem) model and accounting for regional climate and Land-Cover and Land-Use Changes for the 1950-2010 period in April. This data set is lowly to moderately correlated (0.22-0.48) with the satellite Aerosol Optical Depth in April of the 2000s and lowly correlated (0.02-0.11) with the Absorbing Aerosol Index in April of the 1980s, 1990s, and 2000s. The total dust loading is approximately 207.85 Mton per month in April during the recent decade (2000-2014) over dust source regions. Although only the month of April was simulated, results suggest that trends and magnitudes are captured well, using the WRF-Chem-DuMo.

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A long-term Northern Hemisphere snow cover extent data record for climate studies and monitoring

Earth System Science Data ◽

10.5194/essd-7-137-2015 ◽

2015 ◽

Vol 7 (1) ◽

pp. 137-142 ◽

Cited By ~ 107

Author(s):

T. W. Estilow ◽

A. H. Young ◽

D. A. Robinson

Keyword(s):

Snow Cover ◽

Northern Hemisphere ◽

Environmental Data ◽

Climate Data ◽

Data Set ◽

Snow Cover Extent ◽

Data Record ◽

Climate Data Record ◽

Climate Studies

Abstract. This paper describes the long-term, satellite-based visible snow cover extent National Oceanic and Atmospheric Administration (NOAA) climate data record (CDR) currently available for climate studies, monitoring, and model validation. This environmental data product is developed from weekly Northern Hemisphere snow cover extent data that have been digitized from snow cover maps onto a Cartesian grid draped over a polar stereographic projection. The data have a spatial resolution of 190.6 km at 60° latitude, are updated monthly, and span the period from 4 October 1966 to the present. The data comprise the longest satellite-based CDR of any environmental variable. Access to the data is provided in Network Common Data Form (netCDF) and archived by NOAA's National Climatic Data Center (NCDC) under the satellite Climate Data Record Program (doi:10.7289/V5N014G9). The basic characteristics, history, and evolution of the data set are presented herein. In general, the CDR provides similar spatial and temporal variability to its widely used predecessor product. Key refinements included in the CDR improve the product's grid accuracy and documentation and bring metadata into compliance with current standards for climate data records.

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A long-term record of blended satellite and in situ sea-surface temperature for climate monitoring, modeling and environmental studies

Earth System Science Data ◽

10.5194/essd-8-165-2016 ◽

2016 ◽

Vol 8 (1) ◽

pp. 165-176 ◽

Cited By ~ 184

Author(s):

Viva Banzon ◽

Thomas M. Smith ◽

Toshio Mike Chin ◽

Chunying Liu ◽

William Hankins

Keyword(s):

Surface Temperature ◽

Sea Surface Temperature ◽

Large Scale ◽

Sea Surface ◽

Climate Data ◽

Data Set ◽

Volcanic Aerosols ◽

Climate Data Record

Abstract. This paper describes a blended sea-surface temperature (SST) data set that is part of the National Oceanic and Atmospheric Administration (NOAA) Climate Data Record (CDR) program product suite. Using optimum interpolation (OI), in situ and satellite observations are combined on a daily and 0.25° spatial grid to form an SST analysis, i.e., a spatially complete field. A large-scale bias adjustment of the input infrared SSTs is made using buoy and ship observations as a reference. This is particularly important for the time periods when volcanic aerosols from the El Chichón and Mt. Pinatubo eruptions are widespread globally. The main source of SSTs is the Advanced Very High Resolution Radiometer (AVHRR), available from late 1981 to the present, which is also the temporal span of this CDR. The input and processing choices made to ensure a consistent data set that meets the CDR requirements are summarized. A brief history and an explanation of the forward production schedule for the preliminary and science-quality final product are also provided. The data set is produced and archived at the newly formed National Centers for Environmental Information (NCEI) in Network Common Data Form (netCDF) at doi:10.7289/V5SQ8XB5.

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Analysis of variability and long-term trends of sea surface temperature over the China Seas derived from a newly merged regional data set

Climate Research ◽

10.3354/cr01471 ◽

2017 ◽

Vol 73 (3) ◽

pp. 217-231 ◽

Cited By ~ 2

Author(s):

Y Li ◽

L Mu ◽

Y Liu ◽

G Wang ◽

D Zhang ◽

...

Keyword(s):

Surface Temperature ◽

Sea Surface Temperature ◽

Sea Surface ◽

China Seas ◽

Regional Data ◽

Data Set ◽

Long Term Trends ◽

The China Seas

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Climate drivers of plague epidemiology in British India, 1898–1949

Proceedings of The Royal Society B Biological Sciences ◽

10.1098/rspb.2020.0538 ◽

2020 ◽

Vol 287 (1928) ◽

pp. 20200538

Author(s):

Warren S. D. Tennant ◽

Mike J. Tildesley ◽

Simon E. F. Spencer ◽

Matt J. Keeling

Keyword(s):

Predictive Models ◽

Control Measures ◽

Climate Data ◽

British India ◽

Middle Income ◽

Middle Income Countries ◽

Complex Interactions ◽

The World ◽

Spatio Temporal

Plague, caused by Yersinia pestis infection, continues to threaten low- and middle-income countries throughout the world. The complex interactions between rodents and fleas with their respective environments challenge our understanding of human plague epidemiology. Historical long-term datasets of reported plague cases offer a unique opportunity to elucidate the effects of climate on plague outbreaks in detail. Here, we analyse monthly plague deaths and climate data from 25 provinces in British India from 1898 to 1949 to generate insights into the influence of temperature, rainfall and humidity on the occurrence, severity and timing of plague outbreaks. We find that moderate relative humidity levels of between 60% and 80% were strongly associated with outbreaks. Using wavelet analysis, we determine that the nationwide spread of plague was driven by changes in humidity, where, on average, a one-month delay in the onset of rising humidity translated into a one-month delay in the timing of plague outbreaks. This work can inform modern spatio-temporal predictive models for the disease and aid in the development of early-warning strategies for the deployment of prophylactic treatments and other control measures.

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Configurations to Superior Environmental Innovation Strategy: A Both–And Approach

Organization & Environment ◽

10.1177/10860266211031623 ◽

2021 ◽

pp. 108602662110316

Author(s):

Tiziana Russo-Spena ◽

Nadia Di Paola ◽

Aidan O’Driscoll

Keyword(s):

Climate Change ◽

Value Chain ◽

Critical Role ◽

Well Being ◽

Point Of View ◽

Future Generations ◽

Innovation Strategy ◽

Environmental Innovation ◽

Data Set

An effective climate change action involves the critical role that companies must play in assuring the long-term human and social well-being of future generations. In our study, we offer a more holistic, inclusive, both–and approach to the challenge of environmental innovation (EI) that uses a novel methodology to identify relevant configurations for firms engaging in a superior EI strategy. A conceptual framework is proposed that identifies six sets of driving characteristics of EI and two sets of beneficial outcomes, all inherently tensional. Our analysis utilizes a complementary rather than an oppositional point of view. A data set of 65 companies in the ICT value chain is analyzed via fuzzy-set comparative analysis (fsQCA) and a post-QCA procedure. The results reveal that achieving a superior EI strategy is possible in several scenarios. Specifically, after close examination, two main configuration groups emerge, referred to as technological environmental innovators and organizational environmental innovators.

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EXPRESS: How Does Bonus Payment Affect the Demand for Auto Loans and Their Delinquency?

Journal of Marketing Research ◽

10.1177/00222437211009214 ◽

2021 ◽

pp. 002224372110092

Author(s):

Zhenling Jiang ◽

Dennis J. Zhang ◽

Tat Chan

Keyword(s):

Consumer Products ◽

Data Set ◽

Financial Decisions ◽

Consumer Panel ◽

Loan Demand ◽

Bonus Payments ◽

Base Salary ◽

Long Term Impact ◽

Shed Light

This paper studies how receiving a bonus changes the consumers’ demand for auto loans and the risk of future delinquency. Unlike traditional consumer products, auto loans have a long-term impact on consumers’ financial state because of the monthly payment obligation. Using a large consumer panel data set of credit and employment information, the authors find that receiving a bonus increases auto loan demand by 21 percent. These loans, however, are associated with higher risk, as the delinquency rate increases by 18.5 −31.4 percent depending on different measures. In contrast, an increase in consumers’ base salary will increase the demand for auto loans but not the delinquency. By comparing consumers with bonuses with those without bonuses, the authors find that bonus payments lead to both demand expansion and demand shifting on auto loans. The empirical findings help shed light on how consumers make financial decisions and have important implications for financial institutions on when demand for auto loans and the associated risk arise.

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