Geophysical Research Letters最新文献

Applications of process-based models (PBM) for predictions are confounded by multiple uncertainties and computational burdens, resulting in appreciable errors. A novel modeling framework combining a high-fidelity PBM with surrogate and machine learning (ML) models is developed to tackle these challenges and applied for streamflow prediction. A surrogate model permits high computational efficiency of a PBM solution at a minimum loss of its accuracy. A novel probabilistic ML model partitions the PBM-surrogate prediction errors into reducible and irreducible types, quantifying their distributions that arise due to both explicitly perceived uncertainties (such as parametric) or those that are entirely hidden to the modeler (not included or unexpected). Using this approach, we demonstrate a substantial improvement of streamflow predictive accuracy for a case study urbanized watershed. Such a framework provides an efficient solution combining the strengths of high-fidelity and physics-agnostic models for a wide range of prediction problems in geosciences.

Slow slip events (SSEs) are important for the slip budget along a megathrust fault. Although the recurrence of weeks-long short-term SSEs (S-SSEs) in southcentral Alaska has been suggested, a large amount of noise prevented us from detecting discrete events. We applied a systematic detection method to Global Navigation Satellite System data and detected 31 S-SSEs during the 14-year analysis period. The events mainly occurred at a depth from 35 to 45 km at a down-dip extension of the 1964 Alaska earthquake, and the active clusters correlated with the region of the subducting Yakutat microplate. A large cumulative slip of S-SSEs indicated a significant contribution to stress transfer along the plate interface, and its source area spatially coincided with that of the long-term SSEs and the afterslip of the 1964 earthquake. Large and recurrent S-SSEs are key phenomena for understanding interplate slip kinematics in this region.

The Tibetan Plateau (TP) precipitation is experiencing the north-south dipole tendency pattern since 1979. In this study, we identify four primary seasonally evolving patterns (SEPs) that explain approximately 50% of the total variance in precipitation variability over the TP. These SEPs contribute 60%–90% of the spatial mean amplitude of precipitation trends across seasons. In particular, the second SEP that features a north-south dipole pattern dominates the annual mean trend of the precipitation over the TP. The interdecadal variability of the seasonally evolving north-south dipole pattern is linked to the interdecadal variations of summer Silk Road Pattern and Indian monsoon. These findings suggest that the climate variability expressed through SEPs could potentially serve as a significant source for the interdecadal rainfall prediction.

“Land radiative management” (LRM)—intentionally increasing land surface albedo to reduce regional temperatures—has been proposed as a form of geoengineering. Its effects on local precipitation and soil moisture over long timescales are not well understood. We use idealized cloud-permitting simulations and a conceptual model to understand the response of precipitation and soil moisture to a mesoscale albedo anomaly at equilibrium. Initially, differential heating between a high-albedo anomaly and the lower-albedo surrounding environment drives mesoscale circulations, increasing precipitation and soil moisture in the surrounding environment. However, over time, increasing soil moisture reduces the differential heating, eliminating the mesoscale circulations. At equilibrium, the fractional increase in simulated soil moisture is up to 1.3 times the fractional increase in co-albedo (one minus albedo). Thus, LRM may increase precipitation and soil moisture in surrounding regions, enhancing evaporative cooling and spreading the benefits of LRM over a wider region than previously recognized.

A decline of anthropogenic aerosol (AA) emission is expected worldwide over the coming decades. But the climate effects of aerosol removal and greenhouse gases (GHG) emission at regional scale are poorly distinguished and constrained. Taking the Tibetan Plateau (TP) as an instance, analyses of the state-of-the-art climate models participating in the Detection and Attribution Model Intercomparison Project imply that while the observed warming from 1961 to 2020 is predominantly attributed to GHG emission, the future temperature rise will be influenced by the combined effects of persistent increase in GHG concentration and reduction of AA emission. Here, we develop a new constraint method considering the changed contribution of AA forcing. Constrained by detected individual external forcings, the joint contributions of GHG (1.74°C) and AA forcings (0.10°C) will lead to a warming around 1.85°C over the TP during mid-century (2041–2060) relative to 1995–2014 under SSP2-4.5 scenario, which is 0.44°C cooler than the raw projection.

In Greenland, 87% of the glacierized area terminates in the ocean, but mass lost at the ice-ocean interface, or frontal ablation, has not yet been fully quantified. Using measurements and models we calculate frontal ablation of Greenland's 213 outlet and 537 peripheral glaciers and find a total frontal ablation of 481.8 ± 24.0 for 2000–2010 and 510.2 ± 18.6 Gt a⁻¹ for 2010–2020. Ice discharge accounted for ∼90% of frontal ablation during both periods, while mass loss due to terminus retreat comprised the remainder. Only 16 glaciers were responsible for the majority (>50%) of frontal ablation from 2010 to 2020. These estimates, along with the climatic-basal balance, allow for a more complete accounting of Greenland Ice Sheet and peripheral glacier mass balance. In total, Greenland accounted for ∼90% of Northern Hemisphere frontal ablation for 2000–2010 and 2010–2020.

ERA5 reanalysis is used to examine extreme precipitation using a spatially dependent precipitation threshold applied within a cyclone compositing framework. This is used to account for regional variation in precipitation generating processes within Southern Hemisphere mid-latitude cyclones across the cyclone lifecycle. The spatial extent of extreme precipitation is limited to a smaller region around the cyclone center compared to non-extreme precipitation, though extreme precipitation displays a good spatial correlation with non-extreme precipitation. Extreme precipitation occurs more often during the deepening phase of the cyclone before it reaches peak intensity. Precipitation occurrence at the 90th and 98th percentiles reduces to 46% and 30% of the deepening value across the cyclone lifecycle, averaged over the composite. Precipitation fraction at the 90th and 98th percentile reduces to 80% and 60% of the deepening value. Our methodology provides a quantitative assessment of precipitation extremes both spatially and temporally, within a cyclone compositing framework.

Water vapor transport from the South China Sea (SCS) by the marine boundary layer jet (MBLJ) can be an important moisture source for heavy rainfall events in Taiwan during the mei-yu season. However, the variability in the MBLJ due to sea surface temperature (SST) changes and its impact on extreme rainfall events have yet to be well understood. This study investigates how varying the SST over SCS modifies the structure of MBLJ and further impacts an extreme mei-yu rainfall in Taiwan during 1–4 June 2017. Results show that SST over the SCS can affect rainfall in Taiwan through its modulation of the MBLJ. Increasing SST leads to a southward shift of the mei-yu rainfall. This is attributed to the weakening of the MBLJ and the enhanced convection at the leading edge of the mei-yu front. The opposite effect is observed when the SST is decreased but with a smaller impact.

Based on the hourly rainfall gauge data and ERA5 reanalysis for the period 1980–2020, typical synoptic patterns responsible for summer regional hourly extreme precipitation events (RHEPE) over the middle and lower Yangtze River basin have been objectively identified using a circulation clustering method. It is found that the Meiyu front with different locations and intensities imbedded in the East Asian summer monsoon, and landfalling typhoons are the leading contributors. As the dominant synoptic pattern, the Meiyu front pattern is associated with ∼92% of the total RHEPE occurrence and can be categorized into a southerly strong-Meiyu type and a northerly weak-Meiyu type. The RHEPE occurrence shows a predominant morning peak associated with the southerly strong-Meiyu type and a secondary late afternoon peak related to the northerly weak-Meiyu type, in which the Meiyu front is pushed northward by the strengthened western North Pacific subtropical high accompanied by accelerated low-level southwesterly flow.