Abstract The mean circulation pattern and its mechanism over Caiwei Guyot (1,308–5,600 m) in the Northwest Pacific were studied utilizing 3 years of in situ data. A deep anticyclonic cap was found to enclose the entire guyot from its bottom up to a depth of 728 m, which is composed of a stable but highly asymmetric anticyclonic circulation at the foot and a bottom‐trapped anticyclonic circulation over the summit. On the slope, the circulation is complex with a dominant anticyclonic circulation near the bottom and a weak cyclonic circulation at ∼2,200 m. The anticyclonic cap intensity over the summit is significantly modulated by the time‐varying impinging flow. An intensified cold ring above the summit edge was observed at Caiwei Guyot, which differs from the cold domes observed over traditional conic seamounts. Further analysis suggests that the impinging flow is primarily responsible for the cap formation, and the M 2 tide‐seamount interaction plays a secondary role. The anticyclonic cap may play a role in the local geological distribution.
Abstract We present a global dataset of anthropogenic carbon dioxide (CO 2 ) emissions for 343 cities. The dataset builds upon data from CDP (187 cities, few in developing countries), the Bonn Center for Local Climate Action and Reporting (73 cities, mainly in developing countries), and data collected by Peking University (83 cities in China). The CDP data being self-reported by cities, we applied quality control procedures, documented the type of emissions and reporting method used, and made a correction to separate CO 2 emissions from those of other greenhouse gases. Further, a set of ancillary data that have a direct or potentially indirect impact on CO 2 emissions were collected from other datasets (e.g. socio-economic and traffic indices) or calculated (climate indices, urban area expansion), then combined with the emission data. We applied several quality controls and validation comparisons with independent datasets. The dataset presented here is not intended to be comprehensive or a representative sample of cities in general, as the choice of cities is based on self-reporting not a designed sampling procedure.
Standard impoundment operation rules (SIOR) are pre-defined guidelines for refilling reservoirs before the end of the wet season. The advancement and availability of the seasonal flow forecasts provide the opportunity for reservoir operators to use flexible and early impoundment operation rules (EIOR). These flexible impoundment rules can significantly improve water conservation, particularly during dry years. In this study, we investigate the potential application of seasonal streamflow forecasts for employing EIOR in the upper Yangtze River basin. We first define thresholds to determine the streamflow condition in September, which is an important period for decision-making in the basin, and then select the most suitable impoundment operation rules accordingly. The thresholds are used in a simulation–optimization model to evaluate different scenarios for EIOR and SIOR by multiple objectives. We measure the skill of the GloFAS-Seasonal forecast, an operational global seasonal river flow forecasting system, to predict streamflow condition according to the selected thresholds. The results show that: (1) the 20th and 30th percentiles of the historical September flow are suitable thresholds for evaluating the possibility of employing EIOR; (2) compared to climatological forecasts, GloFAS-Seasonal forecasts are skillful for predicting the streamflow condition according to the selected 20th and 30th percentile thresholds; and (3) during dry years, EIOR could improve the fullness storage rate by 5.63% and the annual average hydropower generation by 4.02%, without increasing the risk of flooding. GloFAS-Seasonal forecasts and early reservoir impoundment have the potential to enhance hydropower generation and water utilization.
Abstract Trends in urban fraction around meteorological station were used to quantify the relationship between urban growth and local urban warming rate in temperature records in China. Urban warming rates were estimated by comparing observed temperature trends with those derived from ERA‐Interim reanalysis data. With urban expansion surrounding observing stations, daily minimum temperatures were enhanced, and daily maximum temperatures were slightly reduced. On average, a change in urban fraction from 0% to 100% induces additional warming in daily minimum temperature of +1.7 ± 0.3°C; daily maximum temperature changes due to urbanization are −0.4 ± 0.2°C. Based on this, the regional area‐weighted average trend of urban‐related warming in daily minimum (mean) temperature in eastern China was estimated to be +0.042 ± 0.007 (+0.017 ± 0.003)°C decade −1 , representing about 9% (4%) of overall warming trend and reducing the diurnal temperature range by −0.05°C decade −1 . No significant relationship was found between background temperature anomalies and the strength of urban warming.
According to the data from mountain torrent sites, the geospatial distribution regularity of mountain torrents was first explored. Second, six influencing factors such as relative relief, slope gradient, drainage density, stratigraphy, average annual 24-hour rainfall, and distance to rivers, were chosen to explore the relationship between torrents and these factors. The study area was classified into 179 801 grid cells, and each cell data of six factors was collected using ArcGIS software. Then, the statistical analysis of the quantity distribution and occurrence probability of torrents was carried out. The results showed that both the quantity and density of torrents in the Hanjiang River basin were the largest in Guangdong Province. In terms of administrative division, Meizhou has the largest quantity of torrents while Chaozhou has the highest density. Results also showed that relationships between the occurrence probability of torrents and the relative relief/slope/drainage density were described by y=a1eb1x+a2eb2x with different fitting constants while relationships between the occurrence probability and the stratigraphy/average annual 24-hour rainfall/distance to rivers could be described by y=aebx with different fitting parameters. The study results can provide basis for prevention and control of mountain torrents in Guangdong Province.
On 20 July 2021, a sudden rainstorm happened in central and northern Henan Province, China, killing at least 302 people. This extreme precipitation event incurred substantial socioeconomic impacts and resulted in serious losses. Accurate monitoring of such rainstorm events is crucial. In this study, qualitative and quantitative methods are used to comprehensively evaluate the abilities of 10 high-resolution satellite precipitation products [CMORPH-Raw (Climate Prediction Center morphing technique), CMORPH-RT, PERSIANN-CCS (Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks), GPM IMERG-Early (Integrated Multisatellite Retrievals for Global Precipitation Measurement), GPM IMERG-Late, GSMaP-Now (Global Satellite Mapping of Precipitation), GSMaP-NRT, FY-2F, FY-2G, and FY-2H] in capturing this extreme rainstorm event, as well as their performances in monitoring different precipitation intensities. The results show that these satellite precipitation products are able to capture the spatial distributions of the rainstorm (e.g., its location in central and northern Henan), but all products have underestimated the amount of precipitation in the rainstorm center. With the increase in precipitation intensity, the hit rate decreases, the threat score decreases, and the false alarm rate increases. CMORPH-RT is better at capturing the rainstorm than CMORPH-Raw, and it depictes the rainstorm process well; GPM IMERG-Late is more accurate than GPM IMERG-Early; GSMaP-NRT has performed better than GSMaP-Now; and PERSIANN-CCS and FY-2F perform poorly. Among the products, CMORPH-RT performs the best, which has accurately captured the center of the rainstorm, and is also the closest to the station-based observations. In general, the satellite precipitation products that integrate infrared and passive microwave data are found to be better than those that only make use of infrared data. The satellite precipitation retrieval algorithm and the amount of passive microwave data have a relatively greater impact on the accuracy of satellite precipitation products.
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