Detectable anthropogenic changes in daily-scale circulations driving summer rainfall shifts over eastern China

Wetting in the south while drying in the north during the last few decades constitutes the well-known ‘southern flood–northern drought’ (SFND) precipitation pattern over eastern China. The fingerprint of anthropogenic influence on this dipole pattern of regional precipitation trends has not been confirmed, especially for forced changes in relevant dynamics at the synoptic scale. Using a process-based approach involving model experiments both with and without anthropogenic inputs, it is demonstrated that the occurrences of daily circulation patterns (CPs) governing precipitation over eastern China during 1961–2013 have been altered by human influence. Due to anthropogenic forcing, CPs favoring SFND have become more likely to occur at the expense of CPs unfavorable to SFND. Regression analysis shows that changes recorded in the occurrence of CPs from the factual simulations could explain a large part of the precipitation trends over eastern China. CP frequencies driven by purely natural forcing do not reproduce this dipole pattern nor the inferred magnitude of precipitation trends over eastern China. These results suggest that human influence has played a critical role in shaping the contrasting north–south precipitation trends

Warming effect of dust aerosols modulated by overlapping clouds below

Due to the substantial warming effect of dust aerosols overlying clouds and its poor representation in climate models, it is imperative to accurately quantify the direct radiative forcing (DRF) of above-cloud dust aerosols. When absorbing aerosol layers are located above clouds, the warming effect of aerosols strongly depends on the cloud macro- and micro-physical properties underneath, such as cloud optical depth and cloud fraction at visible wavelength. A larger aerosol-cloud overlap is believed to cause a larger warming effect of absorbing aerosols, but the influence of overlapping cloud fraction and cloud optical depth remains to be explored. In this study, the impact of overlapping cloud properties on the shortwave all-sky DRF due to springtime above-cloud dust aerosols is quantified over northern Pacific Ocean based on 10-year satellite measurements. On average, the DRF is roughly 0.62 Wm^(−2). Furthermore, the warming effect of dust aerosols linearly increases with both overlapping cloud fraction and cloud optical depth. An increase of 1% in overlapping cloud fraction will amplify this warming effect by 1.11 Wm^(−2)τ^(−1). For the springtime northern Pacific Ocean, top-of-atmosphere cooling by dust aerosols turns into warming when overlapping cloud fraction is beyond 0.20. The variation of critical cloud optical depth beyond which dust aerosols switch from exerting a net cooling to a net warming effect depends on the concurrent overlapping cloud fraction. When the overlapping cloud coverage range increases from 0.2 to –0.4 to 0.6–0.8, the corresponding critical cloud optical depth reduces from 6.92 to 1.16. Our results demonstrate the importance of overlapping cloud properties for determining the springtime warming effect of dust aerosols

An updated evaluation of the global mean land surface air temperature and surface temperature trends based on CLSAT and CMST

Past versions of global surface temperature (ST) datasets have been shown to have underestimated the recent warming trend over 1998–2012. This study uses a newly updated global land surface air temperature and a land and marine surface temperature dataset, referred to as China global land surface air temperature (C-LSAT) and China merged surface temperature (CMST), to estimate trends in the global mean ST (combining land surface air temperature and sea surface temperature anomalies) with the data uncertainties being taken into account. Comparing with existing datasets, the statistical significance of the global mean ST warming trend during the past century (1900–2017) remains unchanged, while the recent warming trend during the “hiatus” period (1998–012) increases obviously, which is statistically significant at 95% level when fitting uncertainty is considered as in previous studies (including IPCC AR5) and is significant at 90% level when both fitting and data uncertainties are considered. Our analysis shows that the global mean ST warming trends in this short period become closer among the newly developed global observational data (CMST), remotely sensed/Buoy network infilled datasets, and reanalysis data. Based on the new datasets, the warming trends of global mean land SAT as derived from C-LSAT 2.0 for the period of 1979–2019, 1951–2019, 1900–2019 and 1850–2019 were estimated to be 0.296, 0.219, 0.119 and 0.081 °C/decade, respectively. The warming trends of global mean ST as derived from CMST for the periods of 1998–2019, 1979–2019, 1951–2019 and 1900–2019 were estimated to be 0.195, 0.173, 0.145 and 0.091 °C/decade, respectively

The Assessment of Global Surface Temperature Change from 1850s: The C-LSAT2.0 Ensemble and the CMST-Interim Datasets

Based on C-LSAT2.0, using high- and low-frequency components reconstruction methods, combined with observation constraint masking, a reconstructed C-LSAT2.0 with 756 ensemble members from the 1850s to 2018 has been developed. These ensemble versions have been merged with the ERSSTv5 ensemble dataset, and an upgraded version of the CMST-Interim dataset with 5° × 5° resolution has been developed. The CMST-Interim dataset has significantly improved the coverage rate of global surface temperature data. After reconstruction, the data coverage before 1950 increased from 78%–81% of the original CMST to 81%–89%. The total coverage after 1955 reached about 93%, including more than 98% in the Northern Hemisphere and 81%–89% in the Southern Hemisphere. Through the reconstruction ensemble experiments with different parameters, a good basis is provided for more systematic uncertainty assessment of C-LSAT2.0 and CMST-Interim. In comparison with the original CMST, the global mean surface temperatures are estimated to be cooler in the second half of 19th century and warmer during the 21st century, which shows that the global warming trend is further amplified. The global warming trends are updated from 0.085 ± 0.004°C (10 yr) −1 and 0.128 ± 0.006°C (10 yr) −1 to 0.089 ± 0.004°C (10 yr) −1 and 0.137 ± 0.007°C (10 yr) −1, respectively, since the start and the second half of 20th century

Comprehensive Aerological Reference Data Set (CARDS)

The possibility of anthropogenic climate change has reached the attention of Government officials and researchers. However, one cannot study climate change without climate data. The CARDS project will produce high-quality upper-air data for the research community and for policy-makers. The authors intend to produce a dataset which is: easy to use, as complete as possible, as free of random errors as possible. They will also attempt to identify biases and remove them whenever possible. In this report, they relate progress toward their goal. They created a robust new format for archiving upper-air data, and designed a relational database structure to hold them. The authors have converted 13 datasets to the new format and have archived over 10,000,000 individual soundings from 10 separate data sources. They produce and archive a metadata summary of each sounding they load. They have researched station histories, and have built a preliminary upper-air station history database. They have converted station-sorted data from their primary database into synoptic-sorted data in a parallel database. They have tested and will soon implement an advanced quality-control procedure, capable of detecting and often repairing errors in geopotential height, temperature, humidity, and wind. This unique quality-control method uses simultaneous vertical, horizontal, and temporal checks of several meteorological variables. It can detect errors other methods cannot

Vegetation greening offsets urbanization induced fast warming in Guangdong, Hong Kong, and Macao region (GHMR)

Previous studies show that the environment in the Guangdong, Hong Kong, and Macao region is under the double stress of global warming and urbanization. Here, we show that due to the increase of regional greenness, the effect of urbanization warming on surface air temperature (SAT) decreased with time and became statistically insignificant from 2004 to 2018, compared to 1979 onward; while the urbanization itself has significantly warmed land surface temperature (LST), with a warming rate of 0.14°C ± 0.04°C/10a at daytime and 0.02°C ± 0.02°C/10a at nighttime during 2004–2018, respectively. The anthropogenic heat was found to have a limited influence on SAT, but more significant and tangible effects on LST. It is essential to improve the control of additional warming effects caused by urbanization

Disaster Risks Research and Assessment to Promote Risk Reduction and Management

Natural hazard events lead to disasters when the events interact with exposed and vulnerable physical and social systems. Despite significant progress in scientific understanding of physical phenomena leading to natural hazards as well as of vulnerability and exposure, disaster losses due to natural events do not show a tendency to decrease. This tendency is associated with many factors including increase in populations and assets at risk as well as in frequency and/or magnitude of natural events, especially those related to hydro-meteorological and climatic hazards. But essentially disaster losses increase because some of the elements of the multidimensional dynamic disaster risk system are not accounted for risk assessments. A comprehensive integrated system analysis and periodic assessment of disaster risks at any scale, from local to global, based on knowledge and data/information accumulated so far, are essential scientific tools that can assist in recognition and reduction of disaster risks. This paper reviews and synthesizes the knowledge of natural hazards, vulnerabilities, and disaster risks and aims to highlight potential contributions of science to disaster risk reduction (DRR) in order to provide policy-makers with the knowledge necessary to assist disaster risk mitigation and disaster risk management (DRM)