Atmosphere

Editorial

Jump to: Research

3 pages, 167 KiB

Open AccessEditorial

Application of Homogenization Methods for Climate Records

by Peter Domonkos

Atmosphere 2022, 13(3), 481; https://doi.org/10.3390/atmos13030481 - 15 Mar 2022

Cited by 1 | Viewed by 1526

Abstract

Climate research requires a large amount of fairly accurate observed climatic data [...] Full article

(This article belongs to the Special Issue Application of Homogenization Methods for Climate Records)

Research

Jump to: Editorial

17 pages, 6830 KiB

Open AccessArticle

Potential Influence of the Atlantic Multidecadal Oscillation in the Recent Climate of a Small Basin in Central Mexico

by Martín José Montero-Martínez, Oscar Pita-Díaz and Mercedes Andrade-Velázquez

Atmosphere 2022, 13(2), 339; https://doi.org/10.3390/atmos13020339 - 17 Feb 2022

Cited by 7 | Viewed by 2182

Abstract

One of the main current challenges is detecting changes in the climate at the regional level. The present study tried to address this issue by looking for some influence of large-scale climate oscillations on the climate of a small and complex topography basin [...] Read more.

One of the main current challenges is detecting changes in the climate at the regional level. The present study tried to address this issue by looking for some influence of large-scale climate oscillations on the climate of a small and complex topography basin in Central Mexico. We collected temperature and precipitation data from 44 climate stations within an area of up to 20 km around the Apatlaco River sub-basin (~30 km south of Mexico City) during the period 1950–2013. Posteriorly, quality analysis and homogenization of the climate databases were performed by using the Climatol algorithm. We analyzed the trend of five ETCCDI climate indices through several statistical tests. Finally, we calculated simple Pearson correlations of those indices with four climate oscillation indices that have affected Mexico’s climate in the recent past. The results revealed that the Atlantic Multidecadal Oscillation had a clear influence on four of the five indices analyzed in the study area. The summer days and the extreme maximum and minimum temperatures accounted for a small increase in the temperature of the middle east (urban) basin compared to the middle west (rural), which could be a manifestation of the heat island effect or the difference in soil type (and therefore albedo) of the two zones. As expected, the midsummer drought effect predominated in most of the sub-basin, with only the uppermost part showing monsoon-type precipitation during a typical year. Full article

(This article belongs to the Special Issue Application of Homogenization Methods for Climate Records)

► Show Figures

Figure 1

21 pages, 4925 KiB

Open AccessArticle

Evaluation of the Homogenization Adjustments Applied to European Temperature Records in the Global Historical Climatology Network Dataset

by Peter O’Neill, Ronan Connolly, Michael Connolly, Willie Soon, Barbara Chimani, Marcel Crok, Rob de Vos, Hermann Harde, Peter Kajaba, Peter Nojarov, Rajmund Przybylak, Dubravka Rasol, Oleg Skrynyk, Olesya Skrynyk, Petr Štěpánek, Agnieszka Wypych and Pavel Zahradníček

Atmosphere 2022, 13(2), 285; https://doi.org/10.3390/atmos13020285 - 8 Feb 2022

Cited by 14 | Viewed by 16169

Abstract

The widely used Global Historical Climatology Network (GHCN) monthly temperature dataset is available in two formats—non-homogenized and homogenized. Since 2011, this homogenized dataset has been updated almost daily by applying the “Pairwise Homogenization Algorithm” (PHA) to the non-homogenized datasets. Previous studies found that [...] Read more.

The widely used Global Historical Climatology Network (GHCN) monthly temperature dataset is available in two formats—non-homogenized and homogenized. Since 2011, this homogenized dataset has been updated almost daily by applying the “Pairwise Homogenization Algorithm” (PHA) to the non-homogenized datasets. Previous studies found that the PHA can perform well at correcting synthetic time series when certain artificial biases are introduced. However, its performance with real world data has been less well studied. Therefore, the homogenized GHCN datasets (Version 3 and 4) were downloaded almost daily over a 10-year period (2011–2021) yielding 3689 different updates to the datasets. The different breakpoints identified were analyzed for a set of stations from 24 European countries for which station history metadata were available. A remarkable inconsistency in the identified breakpoints (and hence adjustments applied) was revealed. Of the adjustments applied for GHCN Version 4, 64% (61% for Version 3) were identified on less than 25% of runs, while only 16% of the adjustments (21% for Version 3) were identified consistently for more than 75% of the runs. The consistency of PHA adjustments improved when the breakpoints corresponded to documented station history metadata events. However, only 19% of the breakpoints (18% for Version 3) were associated with a documented event within 1 year, and 67% (69% for Version 3) were not associated with any documented event. Therefore, while the PHA remains a useful tool in the community’s homogenization toolbox, many of the PHA adjustments applied to the homogenized GHCN dataset may have been spurious. Using station metadata to assess the reliability of PHA adjustments might potentially help to identify some of these spurious adjustments. Full article

(This article belongs to the Special Issue Application of Homogenization Methods for Climate Records)

► Show Figures

Figure 1

20 pages, 10034 KiB

Open AccessArticle

Gap Filling and Quality Control Applied to Meteorological Variables Measured in the Northeast Region of Brazil

by Rafaela Lisboa Costa, Heliofábio Barros Gomes, David Duarte Cavalcante Pinto, Rodrigo Lins da Rocha Júnior, Fabrício Daniel dos Santos Silva, Helber Barros Gomes, Maria Cristina Lemos da Silva and Dirceu Luís Herdies

Atmosphere 2021, 12(10), 1278; https://doi.org/10.3390/atmos12101278 - 30 Sep 2021

Cited by 18 | Viewed by 2528

Abstract

In this work, we used the MICE (Multivariate Imputation by Chained Equations) technique to impute missing daily data from six meteorological variables (precipitation, temperature, relative humidity, atmospheric pressure, wind speed and insolation) from 96 stations located in the northeast region of Brazil (NEB) [...] Read more.

In this work, we used the MICE (Multivariate Imputation by Chained Equations) technique to impute missing daily data from six meteorological variables (precipitation, temperature, relative humidity, atmospheric pressure, wind speed and insolation) from 96 stations located in the northeast region of Brazil (NEB) for the period from 1961 to 2014. We then applied tests with a quality control system (QCS) developed for the detection, correction and possible replacement of suspicious data. Both the applied gap filling technique and the QCS showed that it was possible to solve two of the biggest problems found in time series of daily data measured in meteorological stations: the generation of plausible values for each variable of interest, in order to remedy the absence of observations, and how to detect and allow proper correction of suspicious values arising from observations. Full article

(This article belongs to the Special Issue Application of Homogenization Methods for Climate Records)

► Show Figures

Figure 1

16 pages, 5984 KiB

Open AccessEditor’s ChoiceArticle

Relationship between Drought and Precipitation Heterogeneity: An Analysis across Rain-Fed Agricultural Regions in Eastern Gansu, China

by Suping Wang, Qiang Zhang, Jinsong Wang, Yuanpu Liu and Yu Zhang

Atmosphere 2021, 12(10), 1274; https://doi.org/10.3390/atmos12101274 - 29 Sep 2021

Cited by 8 | Viewed by 2275

Abstract

Based on daily meteorological data from 55 meteorological stations in eastern Gansu from 1960 to 2017, the characteristics of the drought process and precipitation heterogeneity were analyzed, and the relationship between drought and precipitation heterogeneity was evaluated. Results showed that there were 1–3 [...] Read more.

Based on daily meteorological data from 55 meteorological stations in eastern Gansu from 1960 to 2017, the characteristics of the drought process and precipitation heterogeneity were analyzed, and the relationship between drought and precipitation heterogeneity was evaluated. Results showed that there were 1–3 drought processes in the study area every year. Drought processes in the eastern and north-central regions were more frequent than those in other regions. Droughts were mainly manifested as intra-seasonal droughts, especially across the spring and summer. PCD (Precipitation Concentration Degree, the concentration degree of the precipitation at a certain time) ranged from 0.2 to 0.7 in the area. PCD increased in spring and autumn but decreased in summer and winter for most regions from 1960 to 2017. PCP (Precipitation Concentration Period, the shortest time which the precipitation was concentrated in) was from late April to early May in spring, mid-to-late July in summer, mid-September in autumn, and late January in winter. In the last 58 years, PCP has remained consistent in most regions, varying by approximately 10 days. In addition to insignificant changes in winter, the days with light and moderate rain presented a declining trend, especially in summer and autumn. The larger the PCD, the fewer the days with light and moderate rain, and the stronger the drought intensity. However, in the east-central region, the larger the PCD in autumn, the weaker was the drought intensity. This difference is related to the PCP and the evapotranspiration. Additionally, the later the PCP, the stronger was the drought intensity, particularly in summer and autumn. When PCD was ≥0.5 in spring and ≥0.4 in summer, the PCP was after May and August in spring and summer, respectively. Droughts appeared in 28–56% of periods when seasonal precipitation was above normal. When PCD was ≥0.5 in autumn and PCP was in early and middle September, droughts appeared in 7% of periods when precipitation was above normal. Our results show that although less precipitation is the leading influencing factor of drought in the dry rain-fed agricultural areas, the influence of precipitation heterogeneity should be also considered for the prediction and diagnosis of seasonal drought. Full article

(This article belongs to the Special Issue Application of Homogenization Methods for Climate Records)

► Show Figures

Figure 1

17 pages, 1617 KiB

Open AccessArticle

Combination of Using Pairwise Comparisons and Composite Reference Series: A New Approach in the Homogenization of Climatic Time Series with ACMANT

by Peter Domonkos

Atmosphere 2021, 12(9), 1134; https://doi.org/10.3390/atmos12091134 - 3 Sep 2021

Cited by 10 | Viewed by 1969

Abstract

The removal of non-climatic biases, so-called inhomogeneities, from long climatic records needs sophistically developed statistical methods. One principle is that the differences between a candidate series and its neighbor series are usually analyzed instead of the candidate series directly, in order to neutralize [...] Read more.

The removal of non-climatic biases, so-called inhomogeneities, from long climatic records needs sophistically developed statistical methods. One principle is that the differences between a candidate series and its neighbor series are usually analyzed instead of the candidate series directly, in order to neutralize the possible impacts of regionally common natural climate variation on the detection of inhomogeneities. In most homogenization methods, two main kinds of time series comparisons are applied, i.e., composite reference series or pairwise comparisons. In composite reference series, the inhomogeneities of neighbor series are attenuated by averaging the individual series, and the accuracy of homogenization can be improved by the iterative improvement of composite reference series. By contrast, pairwise comparisons have the advantage that coincidental inhomogeneities affecting several station series in a similar way can be identified with higher certainty than with composite reference series. In addition, homogenization with pairwise comparisons tends to facilitate the most accurate regional trend estimations. A new time series comparison method is presented here, which combines the use of pairwise comparisons and composite reference series in a way that their advantages are unified. This time series comparison method is embedded into the Applied Caussinus-Mestre Algorithm for homogenizing Networks of climatic Time series (ACMANT) homogenization method, and tested in large, commonly available monthly temperature test datasets. Further favorable characteristics of ACMANT are also discussed. Full article

(This article belongs to the Special Issue Application of Homogenization Methods for Climate Records)

► Show Figures

Figure 1

32 pages, 19856 KiB

Open AccessArticle

Sensitivity of Change-Point Detection and Trend Estimates to GNSS IWV Time Series Properties

by Khanh Ninh Nguyen, Annarosa Quarello, Olivier Bock and Emilie Lebarbier

Atmosphere 2021, 12(9), 1102; https://doi.org/10.3390/atmos12091102 - 26 Aug 2021

Cited by 9 | Viewed by 2224

Abstract

This study investigates the sensitivity of the GNSSseg segmentation method to change in: GNSS data processing method, length of time series (17 to 25 years), auxiliary data used in the integrated water vapor (IWV) conversion, and reference time series used in the segmentation [...] Read more.

This study investigates the sensitivity of the GNSSseg segmentation method to change in: GNSS data processing method, length of time series (17 to 25 years), auxiliary data used in the integrated water vapor (IWV) conversion, and reference time series used in the segmentation (ERA-Interim versus ERA5). Two GNSS data sets (IGS repro1 and CODE REPRO2015), representative of the first and second IGS reprocessing, were compared. Significant differences were found in the number and positions of detected change-points due to different a priori ZHD models, antenna/radome calibrations, and mapping functions. The more recent models used in the CODE solution have reduced noise and allow the segmentation to detect smaller offsets. Similarly, the more recent reanalysis ERA5 has reduced representativeness errors, improved quality compared to ERA-Interim, and achieves higher sensitivity of the segmentation. Only 45–50% of the detected change-points are similar between the two GNSS data sets or between the two reanalyses, compared to 70–80% when the length of the time series or the auxiliary data are changed. About 35% of the change-points are validated with respect to metadata. The uncertainty in the homogenized trends is estimated to be around 0.01–0.02 kg m

^{- 2}

year

^{- 1}

. Full article

(This article belongs to the Special Issue Application of Homogenization Methods for Climate Records)

► Show Figures

Figure 1

11 pages, 4033 KiB

Open AccessArticle

A Statistical Analysis of Daily Snow Depth Trends in North America

by Jonathan Woody, Yang Xu, Jamie Dyer, Robert Lund and Anuradha P. Hewaarachchi

Atmosphere 2021, 12(7), 820; https://doi.org/10.3390/atmos12070820 - 27 Jun 2021

Cited by 2 | Viewed by 1668

Abstract

Several attempts to assess regional snow depth trends have been previously made. These studies estimate trends by applying various statistical methods to snow depths, new snowfalls, or their climatological proxies such as snow water equivalents. In most of these studies, inhomogeneities (changepoints) were [...] Read more.

Several attempts to assess regional snow depth trends have been previously made. These studies estimate trends by applying various statistical methods to snow depths, new snowfalls, or their climatological proxies such as snow water equivalents. In most of these studies, inhomogeneities (changepoints) were not accounted for in the analysis. Changepoint features can dramatically influence trend inferences from climate time series. The purpose of this paper is to present a detailed statistical methodology to estimate trends of a time series of daily snow depths that account for changepoint features. The methods are illustrated in the analysis of a daily snow depth data set from North America. Full article

(This article belongs to the Special Issue Application of Homogenization Methods for Climate Records)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Application of Homogenization Methods for Climate Records

Share This Special Issue

Special Issue Editor

Special Issue Information

Keywords

Published Papers (8 papers)

Editorial

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI