Influence of Precipitation Changes on the SPI and Related Drought Severity. An Analysis Using Long-Term Data Series

Abstract. Long-term data series (1996–2009) for eleven acidic headwater streams (< 10 km2) in Sweden were analyzed to determine factors controlling concentrations of trace metals. In-stream chemical data as well climatic, flow, and deposition chemistry data were used to develop models predicting concentrations of chromium (Cr), lead (Pb), and zinc (Zn). Data were initially analyzed using partial least squares to determine a set of variables that could predict metal concentrations across all sites. Organic matter (as absorbance) and iron related positively to Pb and Cr, while pH related negatively to Pb and Zn. Other variables such as conductivity, manganese, and temperature were important as well. Multiple linear regression was then used to determine minimally adequate prediction models which explained an average of 35% (Cr), 52% (Zn), and 72% (Pb) of metal variation across all sites. While models explained at least 50% of variation in the majority of sites for Pb (10) and Zn (8), only three sites met this criterion for Cr. Investigation of variation between site models for each metal revealed geographical (altitude), chemical (sulfate), and land-use (silvaculture) influences on predictive power of the models. Residual analysis revealed seasonal differences in the ability of the models to predict metal concentrations as well. Expected future changes in model variables were applied and results showed the potential for long-term increases (Pb) or decreases (Zn) for trace metal concentrations at these sites.

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Performance of Drought Indices in Trichy Region, Tamil Nadu

Current Journal of Applied Science and Technology ◽

10.9734/cjast/2019/v38i530385 ◽

2019 ◽

pp. 1-10

Author(s):

L. Sathya ◽

R. Lalitha

Keyword(s):

Tamil Nadu ◽

Standardized Precipitation Index ◽

Synthetic Data ◽

Meteorological Drought ◽

Severity Index ◽

Rainfall Anomaly ◽

Drought Indices ◽

Drought Severity ◽

Data Series

Droughts are regional phenomena, which are considered as one of the major natural environmental hazards and severely affect the water resources. Climate variability may result in harmful drought periods in semiarid regions. Meteorological drought indices are considered as important tools for drought monitoring, they are embedded with different theoretical and experimental structures. This study compares the performance of three indices of Standardized Precipitation Index (SPI), Rainfall Anomaly Index (RAI) End Palmer Drought Severity Index (PNPI) to predict long-term drought events using the Thomas-Feiring Model and historical data. For studies of areal drought extent, the 61 years (1951-2011) historical rainfall data of Trichy District were utilized to generate 58 years (2012-2070) synthetic data series so that the characteristics of long-term drought might be determined and the performance of those three indices might be analyzed and compared. The results show that SPI and PNPI perform similarly with regard to drought identification and detailed analysis to determine the characteristics of long-term drought. Finally, the RAI indicated significant deviations from normalized natural processes.

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Analysis of Trends in the FireCCI Global Long Term Burned Area Product (1982–2018)

Fire ◽

10.3390/fire4040074 ◽

2021 ◽

Vol 4 (4) ◽

pp. 74

Author(s):

Gonzalo Otón ◽

José Miguel C. Pereira ◽

João M. N. Silva ◽

Emilio Chuvieco

Keyword(s):

Time Series ◽

Temporal Trends ◽

European Space Agency ◽

Eastern Africa ◽

Burned Area ◽

Data Series ◽

Short Term ◽

The Impact ◽

Term Data

We present an analysis of the spatio-temporal trends derived from long-term burned area (BA) data series. Two global BA products were included in our analysis, the FireCCI51 (2001–2019) and the FireCCILT11 (1982–2018) datasets. The former was generated from Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m reflectance data, guided by 1 km active fires. The FireCCILT11 dataset was generated from Land Long-Term Data Record data (0.05°), which provides a consistent time series for Advanced Very High Resolution Radiometer images, acquired from the NOAA satellite series. FireCCILT11 is the longest time series of a BA product currently available, making it possible to carry out temporal analysis of long-term trends. Both products were developed under the FireCCI project of the European Space Agency. The two datasets were pre-processed to correct for temporal autocorrelation. Unburnable areas were removed and the lack of the FireCCILT11 data in 1994 was examined to evaluate the impact of this gap on the BA trends. An analysis and comparison between the two BA products was performed using a contextual approach. Results of the contextual Mann-Kendall analysis identified significant trends in both datasets, with very different regional values. The long-term series presented larger clusters than the short-term ones. Africa displayed significant decreasing trends in the short-term, and increasing trends in the long-term data series, except in the east. In the long-term series, Eastern Africa, boreal regions, Central Asia and South Australia showed large BA decrease clusters, and Western and Central Africa, South America, USA and North Australia presented BA increase clusters.

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Government expenditure in New Zealand since 1935: a preliminary reassessment

Policy Quarterly ◽

10.26686/pq.v13i2.4664 ◽

2017 ◽

Vol 13 (2) ◽

Author(s):

Matthew Gibbons

Keyword(s):

New Zealand ◽

Comparative Studies ◽

Government Expenditure ◽

Data Series ◽

Optimal Size ◽

Economic Issue ◽

Size Of Government ◽

Expenditure Data ◽

Term Data

The optimal size of government is an important political and economic issue. However, because no long-term government expenditure series has official standing, New Zealand is often a missing case in comparative studies of government expenditure (Castles, 1998). Although government expenditure data is available from 1972 on Treasury’s website (New Zealand Treasury, 2016), the most widely used data before 1972 is a ‘consolidated’ long-term data series, on Statistics New Zealand’s website, which uses data from a number of sources and is published with strong disclaimers.

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Generating a long-term data series of burned area in Eastern Siberia using LTDR data (1984–2016)

Remote Sensing Letters ◽

10.1080/2150704x.2019.1637958 ◽

2019 ◽

Vol 10 (10) ◽

pp. 1008-1017 ◽

Cited By ~ 1

Author(s):

Oleg Tomshin ◽

Vladimir Solovyev

Keyword(s):

Burned Area ◽

Data Series ◽

Eastern Siberia ◽

Term Data

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Trends, drivers, and lessons from a long-term data series of the Asturian (northern Spain) gooseneck barnacle territorial use rights system

Bulletin of Marine Science ◽

10.5343/bms.2015.1080 ◽

2017 ◽

Vol 93 (1) ◽

pp. 35-51 ◽

Cited By ~ 8

Author(s):

Antonella Rivera ◽

Stefan Gelcich ◽

Lucía García-Flórez ◽

José Luis Acuña

Keyword(s):

Data Series ◽

Northern Spain ◽

Gooseneck Barnacle ◽

Term Data

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Zoobenthic biomass limited by phytoplankton abundance: evidence from parallel changes in two long-term data series in the Wadden Sea

Journal of Sea Research ◽

10.1016/s1385-1101(02)00162-4 ◽

2002 ◽

Vol 48 (2) ◽

pp. 111-125 ◽

Cited By ~ 53

Author(s):

J.J Beukema ◽

G.C Cadée ◽

R Dekker

Keyword(s):

Wadden Sea ◽

Data Series ◽

Phytoplankton Abundance ◽

Term Data

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Long term changes of the sub-daily precipitation extremes in Hungary

10.5194/ems2021-251 ◽

2021 ◽

Author(s):

Monika Lakatos ◽

Olivér Szentes

Keyword(s):

Extreme Precipitation ◽

Daily Precipitation ◽

Heavy Precipitation ◽

Data Series ◽

Precipitation Frequency ◽

Maximum Rainfall ◽

Extreme Precipitation Events ◽

Digital Database ◽

Precipitation Changes

The warming climate evokes increasing frequency of extreme precipitation in some region. Analysis of long-term measurements could support the better understanding of the processes that cause extreme precipitation events.Automatic stations replaced the ombrometer in many places in Hungary, particularly from the late 1990s. The change of the measurement practice do not allow simply merging the data recorded form the registering paper in the past and the recent 10 minutes measurements.&#160; &#160;The most intense 5, 10, 20, 30, 60, 180 min sub-totals per rainfall events were recorded from the ombrometer registering paper before atomization, typically until 1993. By contrast, the 10 min precipitation sum from the AWSs are stored in the meteorological database of the Hungarian Meteorological Service from automatization. In order to join together the older and the AWS measurements it was necessary to develop a method to make this possible. Therefore we downscaled the 10 min data in time. The sampling of the AWSs is one minute, although the 1-minute data are available only for some stations in the digital database. &#160;We applied a linear regression model to downscale the 10-miniute data for 1 min. After this, we can derive the most intense sub-totals per events from the AWS data as if they have been measured with the ombrometers.Thereby a set of sub-daily precipitation indices defined in the INTENSE project (https://research.ncl.ac.uk/intense/aboutintense/ can be computed for longer data series. Some of the indices specified in INTENSE project describes the maximum rainfall totals and timing, the intensity, duration and frequency of heavy precipitation, frequency of rainfall above specific thresholds and some of them is related to diurnal cycle. A few of these indices are analysed for long data series to detect the sub-daily precipitation changes in Hungary.

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An update on the uncertainties of water vapor measurements using Cryogenic Frostpoint Hygrometers

10.5194/amt-2016-44 ◽

2016 ◽

Author(s):

Holger Vömel ◽

Tatjana. Naebert ◽

Ruud Dirksen ◽

Michael Sommer

Keyword(s):

Water Vapor ◽

Data Series ◽

Climate Variables ◽

Stratospheric Water Vapor ◽

Tropospheric Measurements ◽

Long Time ◽

Climate Series ◽

Term Data ◽

Better Than

Abstract. Long time series of observations of essential climate variables in the troposphere and stratosphere are often impacted by inconsistencies in instrumentation and ambiguities in the interpretation of the data. To reduce these problems of long term data series all measurements should include an estimate of their uncertainty and a description of their sources. Here we present an update of the uncertainties for tropospheric and stratospheric water vapor observations using the Cryogenic Frostpoint Hygrometer (CFH). The largest source of measurement uncertainty is the controller stability, which is discussed here in detail. We describe a method to quantify this uncertainty for each profile based on the measurements. We also show the importance of a manufacturer independent ground check, which is an essential tool to continuously monitor the uncertainty introduced by instrument variability. A small bias, which has previously been indicated in lower tropospheric measurements, is described here in detail and has been rectified. Under good conditions the total from all sources of uncertainty of frostpoint or dewpoint measurements using the CFH can be better than 0.2 K. Systematic errors, which are most likely to impact long term climate series are verified to be less than 0.1 K.

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