Rain-season trends in precipitation and their effect in different climate regions of China during 1961–2008

Song, Yanling; Achberger, Christine; Linderholm, Hans W.

doi:10.1088/1748-9326/6/3/034025

Cited by 86 publications

(56 citation statements)

References 19 publications

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“…Similar situations have been detected in most subtropical and tropical monsoon climate regions of southeastern China during 1960−2000, where the number of days with rain > 50 mm showed a slightly positive trend, while precipitation days with light rain (<10 mm) decreased (Song et al 2011, Liu et al 2011). …”

Section: The Presentsupporting

confidence: 80%

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Observed and projected changes in rainfall extremes in the Metropolitan Area of São Paulo

Marengo¹,

Valverde²,

Obregón³

2013

Clim. Res.

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Changes in rainfall extremes and flooding are becoming more frequent in many countries, particularly in large cities where people and assets are concentrated. In the Metropolitan Area of the city of São Paulo (MASP) region, heavy or extreme precipitation events have important effects on society. Flash floods and landslides, associated with intense, but often brief, rainfall events, may be the most destructive of extreme events. Observations since the mid-1930s in the MASP region have shown significant increases in total and heavy rainfall and decreases in light rain. This was probably due to natural climate variability, but with some signals of the urbanization effect, especially during the last 40 yr. Here projections of future changes in rainfall extremes in the MASP region were derived from the Eta-CPTEC 40 km regional model nested in the HadCM3 global model, with 4 available realizations of the global model for the A1B emissions scenario to the end of the 21st century. Trends were assessed for significance using the nonparametric Mann-Kendall test. Projections, based on percentiles and on the number of days with rainfall above a certain limit, suggested: (a) an increase in total precipitation, (b) an increase in heavy precipitation and in the contribution to total precipitation from more intense rainfall events, and (c) the possibility of longer dry periods separating days with intense rain in the MASP region. The trends were stronger and more significant in the second half of the 21st century. We are aware that dynamical downscaling may not provide information at the weather station level and that climate modeling does not resolve all uncertainties. However, we believe that this exercise enables climate assessments that, in time, can be used for general public information.

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Section: The Presentsupporting

confidence: 80%

“…As suggested by Song et al (2011), changes in the total amount of rainy-season precipitation are manifested in different ways -i.e. by variations in the number of wet days, by variations in precipitation intensity, or by both.…”

Section: Introductionmentioning

confidence: 99%

Observed and projected changes in rainfall extremes in the Metropolitan Area of São Paulo

Marengo¹,

Valverde²,

Obregón³

2013

Clim. Res.

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“…Furthermore, different sources influence the aerosol content in different parts of China and in different seasons, i.e., dust emission in the west in the spring, biomass burning in the summer/autumn seasons in eastern China and the emissions of VOCs from vegetated areas (e.g., Tan et al, 2015). The effects of these emissions are augmented by the meteorological conditions which also vary by region and season (e.g., Ding and Murakami, 1994;Domros and Peng, 1988;Song et al, 2011;Jiang et al, 2015) and large-scale periodic climate variability (e.g., Liu et al, 2013).…”

Section: Discussionmentioning

confidence: 99%

Two decades of satellite observations of AOD over mainland China using ATSR-2, AATSR and MODIS/Terra: data set evaluation and large-scale patterns

et al. 2018

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Abstract. The retrieval of aerosol properties from satellite observations provides their spatial distribution over a wide area in cloud-free conditions. As such, they complement ground-based measurements by providing information over sparsely instrumented areas, albeit that significant differences may exist in both the type of information obtained and the temporal information from satellite and ground-based observations. In this paper, information from different types of satellite-based instruments is used to provide a 3-D climatology of aerosol properties over mainland China, i.e., vertical profiles of extinction coefficients from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), a lidar flying aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite and the columnintegrated extinction (aerosol optical depth -AOD) available from three radiometers: the European Space Agency (ESA)'s Along-Track Scanning Radiometer version 2 (ATSR-2), Advanced Along-Track Scanning Radiometer (AATSR) (together referred to as ATSR) and NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra satellite, together spanning the period 1995-2015. AOD data are retrieved from ATSR using the ATSR dual view (ADV) v2.31 algorithm, while for MODIS Collection 6 (C6) the AOD data set is used that was obtained from merging the AODs obtained from the dark target (DT) and deep blue (DB) algorithms, further referred to as the DTDB merged AOD product. These data sets are validated and differences are compared using Aerosol Robotic Network (AERONET) version 2 L2.0 AOD data as reference. The results show that, over China, ATSR slightly underestimates the AOD and MODIS slightly overestimates the AOD. Consequently, ATSR AOD is overall lower than that from MODIS, and the difference increases with increasing AOD. The comparison also shows that neither of the ATSR and MODIS AOD data sets is better than the other one everywhere. However, ATSR ADV has limitations over bright surfaces which the MODIS DB was designed for. To allow for comparison of MODIS C6 results with previous analyses where MODIS Collection 5.1 (C5.1) data were used, also the difference between the C6 and C5.1 merged DTDB data sets from MODIS/Terra over China is briefly discussed.The AOD data sets show strong seasonal differences and the seasonal features vary with latitude and longitude across China. Two-decadal AOD time series, averaged over all of mainland China, are presented and briefly discussed. Using the 17 years of ATSR data as the basis and MODIS/Terra to follow the temporal evolution in recent years when the environmental satellite Envisat was lost requires a compariPublished by Copernicus Publications on behalf of the European Geosciences Union.

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“…The difference in the seasonal variation of the AOD between regions 1 (NCP) and 5 and those further south in region 2 (YRD) and region 7 (PRD), which are all very large urban areas with a high population and large industrial development, is likely due to the different climatological zones. The NCP is situated in a temperate monsoon climate region, the YRD in a subtropical monsoon climate region and region 7 combines regions with a subtropical and a tropical monsoon climate, with strong differences in rain-season trends, i.e., precipitation and number of rain days (Song et al, 2011;Kourtidis et al, 2015;Stathopoulos et al, 2017). The East Asian summer monsoon (EASM) and the associated rain patterns over eastern China (Song et al, 2011) progress from the south in April to the YRD in the early summer and reach BTH in July.…”

Section: Seasonal Variation By Region For the 2000-2011 Periodmentioning

confidence: 99%

Spatial and seasonal variations of aerosols over China from two decades of multi-satellite observations – Part 1: ATSR (1995–2011) and MODIS C6.1 (2000–2017)

et al. 2018

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Abstract. Aerosol optical depth (AOD) patterns and interannual and seasonal variations over China are discussed based on the AOD retrieved from the Along-Track Scanning Radiometer (ATSR-2, 1995(ATSR-2, -2002, the Advanced ATSR (AATSR, 2002(AATSR, -2012) (together ATSR) and the MODerate resolution Imaging Spectroradiometer (MODIS) aboard the Terra satellite (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017). The AOD products used were the ATSR Dual View (ADV) v2.31 AOD and the MODIS/Terra Collection 6.1 (C6.1) merged dark target (DT) and deep blue (DB) AOD product. Together these datasets provide an AOD time series for 23 years, from 1995 to 2017. The difference between the AOD values retrieved from ATSR-2 and AATSR is small, as shown by pixel-by-pixel and monthly aggregate comparisons as well as validation results. This allows for the combination of the ATSR-2 and AATSR AOD time series into one dataset without offset correction.ADV and MODIS AOD validation results show similar high correlations with the Aerosol Robotic Network (AERONET) AOD (0.88 and 0.92, respectively), while the corresponding bias is positive for MODIS (0.06) and negative for ADV ( − 0.07). Validation of the AOD products in similar conditions, when ATSR and MODIS/Terra overpasses are within 90 min of each other and when both ADV and MODIS retrieve AOD around AERONET locations, show that ADV performs better than MODIS in autumn, while MODIS performs slightly better in spring and summer. In winter, both ADV and MODIS underestimate the AERONET AOD.Similar AOD patterns are observed by ADV and MODIS in annual and seasonal aggregates as well as in time series. ADV-MODIS difference maps show that MODIS AOD is generally higher than that from ADV. Both ADV and MODIS show similar seasonal AOD behavior. The AOD maxima shift from spring in the south to summer along the eastern coast further north.The agreement between sensors regarding year-to-year AOD changes is quite good. between ATSR and MODIS with regards to the AOD tendencies in the overlapping period is rather strong in summer, autumn and overall for the yearly average; however, in winter and spring, when there is a difference in coverage between the two instruments, the agreement between ATSR and MODIS is lower.AOD tendencies in China during the 1995-2017 period will be discussed in more detail in Part 2 (a following paper: Sogacheva et al., 2018), where a method to combine AOD time series from ADV and MODIS is introduced, and combined AOD time series are analyzed.

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Rain-season trends in precipitation and their effect in different climate regions of China during 1961–2008

Cited by 86 publications

References 19 publications

Observed and projected changes in rainfall extremes in the Metropolitan Area of São Paulo

Observed and projected changes in rainfall extremes in the Metropolitan Area of São Paulo

Two decades of satellite observations of AOD over mainland China using ATSR-2, AATSR and MODIS/Terra: data set evaluation and large-scale patterns

Spatial and seasonal variations of aerosols over China from two decades of multi-satellite observations – Part 1: ATSR (1995–2011) and MODIS C6.1 (2000–2017)

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