A new linear and conservative finite difference scheme for the Gross–Pitaevskii equation with angular momentum rotation

A new linear and conservative finite difference scheme which preserves discrete mass and energy is developed for the two-dimensional Gross–Pitaevskii equation with angular momentum rotation. In addition to the energy estimate method and mathematical induction, we use the lifting technique as well as some well-known inequalities to establish the optimal $H^{1}$-error estimate for the proposed scheme with no restrictions on the grid ratio. Unlike the existing numerical solutions which are of second-order accuracy at the most, the convergence rate of the numerical solution is proved to be of order $O(h^4+\tau^2)$ with time step $\tau$ and mesh size $h$. Numerical experiments have been carried out to show the efficiency and accuracy of our new method. doi:10.1017/S144618111900002

The Spatiotemporal Characteristics of Wildfires across Australia and Their Connections to Extreme Climate Based on a Combined Hydrological Drought Index

With the frequent occurrence of extreme climates around the world, the frequency of regional wildfires is also on the rise, which poses a serious threat to the safety of human life, property, and regional ecosystems. To investigate the role of extreme climates in the occurrence and spread of wildfires, we combined precipitation, evapotranspiration, soil moisture (SM), maximum temperature (MT), relative humidity, plant canopy water, vapor pressure deficit, and a combined hydrological drought index based on six Gravity Recovery and Climate Experiment (GRACE) and its follow-on (GRACE-FO) products to study the relationship between climate change and wildfires across Australia between 2003 and 2020. The results show that Australia’s wildfires are mainly concentrated in the northern region, with a small number being distributed along the southeastern coast. The high burned months are September (2.5941 × 106 ha), October (4.9939 × 106 ha), and November (3.8781 × 106 ha), while the years with a larger burned area are 2011 (79.95 × 106 ha) and 2012 (78.33 × 106 ha) during the study period. On a seasonal scale, the terrestrial water storage change and the hydrometeorological factors have the strong correlations with burned area, while for only the drought index, SM and MT are strongly related to burned area on an interannual scale. By comparing the data between the high burned and normal years, the impact of droughts on wildfires is achieved through two aspects: (1) the creation of a dry atmospheric environment, and (2) the accumulation of natural combustibles. Extreme climates affect wildfires through the occurrence of droughts. Among them, the El Niño–Southern Oscillation has the greatest impact on drought in Australia, followed by the Pacific Decadal Oscillation and the Indian Ocean Dipole (correlation coefficients are −0.33, −0.31, and −0.23, respectively), but there is little difference among the three. The proposed hydrological drought index in our study has the potential to provide an early warning of regional wildfires. Our results have a certain reference significance for comprehensively understanding the impact mechanism of extreme climates on regional wildfires and for establishing an early warning system for regional wildfires

The Drought Events over the Amazon River Basin from 2003 to 2020 Detected by GRACE/GRACE-FO and Swarm Satellites

The climate anomaly in the Amazon River basin (ARB) has a very important influence on global climate change and has always been the focus of scientists from all over the world. To fill the 11-month data gap between Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) missions, we fused the TWSC results from six GRACE solutions by using the generalized three-cornered hat and the least square method to improve the reliability of TWSC results, and then combined Swarm data to construct an uninterrupted long time series of a TWSC-based drought index (GRACE/Swarm-DSI). The drought index was used to detect and characterize the drought events in the ARB between 2003 and 2020. The results show that GRACE/Swarm-DSI has a strong correlation with Self-Calibrating Palmer Drought Severity Index (SCPDSI) (0.6345), Standardized Precipitation Evapotranspiration Index-3 (SPEI-3) (0.5411), SPEI-6 (0.6377) and SPEI-12 (0.6820), and the Nash–Sutcliffe efficiency between GRACE/Swarm-DSI and the above four drought indices are 0.3348, 0.2786, 0.4044 and 0.4627, respectively. Eleven drought events were identified in the ARB during the study period, and the 2005, 2010 and 2016 droughts are the most severe and the longest. The correlation between GRACE/Swarm-DSI and precipitation (PPT) (the correlation coefficient is 0.55 with a 2-month delay) is higher than that of evapotranspiration (ET) (the correlation coefficient is −0.18 with a 12-month delay). It explains that less PPT is the main cause of drought events in the ARB. The influence of PPT is greater in the plains than the one in the mountains and the response time of GRACE/Swarm-DSI to PPT is 1~2 months in most regions. Our results provide a certain reference for the hydrological application of the Swarm model in filling the gap between GRACE and GRACE-FO missions

Natural- and Human-Induced Influences on Terrestrial Water Storage Change in Sichuan, Southwest China from 2003 to 2020

A quantitative understanding of changes in water resources is crucial for local governments to enable timely decision-making to maintain water security. Here, we quantified natural-and human-induced influences on the terrestrial water storage change (TWSC) in Sichuan, Southwest China, with intensive water consumption and climate variability, based on the data from the Gravity Recovery and Climate Experiment (GRACE) and its Follow-on (GRACE-FO) during 2003–2020. We combined the TWSC estimates derived from six GRACE/GRACE-FO solutions based on the uncertainties of each solution estimated from the generalized three-cornered hat method. Metrics of correlation coefficient and contribution rate (CR) were used to evaluate the influence of precipitation, evapotranspiration, runoff, reservoir storage, and total water consumption on TWSC in the entire region and its five economic regions. The results showed that a significant improvement in the fused TWSC was found compared to those derived from a single model. The increase in regional water storage with a rate of 3.83 ± 0.54 mm/a was more influenced by natural factors (CR was 53.17%) compared to human influence (CR was 46.83%). Among the factors, the contribution of reservoir storage was the largest (CR was 42.32%) due to the rapid increase in hydropower stations, followed by precipitation (CR was 35.16%), evapotranspiration (CR was 15.86%), total water consumption (CR was 4.51%), and runoff (CR was 2.15%). Among the five economic regions, natural influence on Chengdu Plain was the highest (CR was 48.21%), while human influence in Northwest Sichuan was the largest (CR was 61.37%). The highest CR of reservoir storage to TWSC was in Northwest Sichuan (61.11%), while the highest CRs of precipitation (35.16%) and evapotranspiration (15.86%) were both in PanXi region. The results suggest that TWSC in Sichuan is affected by natural factors and intense human activities, in particular, the effect of reservoir storage on TWSC is very significant. Our study results can provide beneficial help for the management and assessment of regional water resources