Related papers: The Arctic surface climate in CMIP6: status and de…
Data-driven machine learning models for weather forecasting have made transformational progress in the last 1-2 years, with state-of-the-art ones now outperforming the best physics-based models for a wide range of skill scores. Given the…
As IPCC ARs stated, global warming is estimated based on the average from 1850 to 1900 (global average temperature of preindustrialization estimated from relatively sparse observations). Given the impossibility of massive increasing…
In this article, we considered the problem of sea ice cover is melting. Considering the `satellite passive microwave remote sensing data' as functional data, we studied daily observation of sea ice cover of each year as a smooth continuous…
Changing climate conditions threaten the natural permafrost thaw-freeze cycle, leading to year-round soil temperatures above 0{\deg}C. In Alaska, the warming of the topmost permafrost layer, known as the active layer, signals elevated…
This work investigates climate--projections over a transitional region between dry and wet climates, the Iberian Peninsula (IP). With this purpose, the Weather Research and Forecasting (WRF) model, driven CCSM4 and MPI-ESM-LR GCMs…
The rapidly shrinking Arctic sea ice is changing weather patterns and disrupting the balance of nature. Dynamics of Arctic weather variability (WV) plays a crucial role in weather forecasting and is closely related to extreme weather…
Arctic sea ice extent has drawn increasing interest and alarm from geoscientists, owing to its rapid decline. In this article, we propose a Bayesian spatio-temporal hierarchical statistical model for binary Arctic sea ice data over two…
The thermal dynamics and hydrology of active layer soils and supra-permafrost aquifers determine the fate of the vast pool of carbon that they hold. In permafrost watersheds of Arctic Alaska, air temperature has warmed by up to 3.5 {\deg}C…
To analyze climate change mitigation strategies, economists rely on simplified climate models - climate emulators. We propose a generic and transparent calibration and evaluation strategy for these climate emulators that is based on Coupled…
Increased research interest and economic activity in the Arctic raise the need for new observations of sea ice dynamics. Remote sensing as well as mathematical and numerical models of wave propagation in sea ice would benefit from more in…
The debate over the early Martian climate is among the most intriguing in planetary science. Although the geologic evidence generally supports a warmer and wetter climate, climate models have had difficulty simulating such a scenario,…
In light of the rapid recent retreat of Arctic sea ice, the extreme weather events triggering the variability in Arctic ice cover has drawn increasing attention. A non-Gaussian $\alpha$-stable L\'evy process is thought to be an appropriate…
Climate models have been key for assessing the impact of climate change and simulating future climate scenarios. The machine learning (ML) community has taken an increased interest in supporting climate scientists' efforts on various tasks…
Quantitative assessment of climate change risk requires a method for constructing probabilistic time series of changes in physical climate parameters. Here, we develop two such methods, Surrogate/Model Mixed Ensemble (SMME) and Monte Carlo…
Machine learning weather models trained on observed atmospheric conditions can outperform conventional physics-based models at short- to medium-range (1-14 day) forecast timescales. Here we take the machine learning weather model ACE2,…
Variability in sea ice conditions, combined with strong couplings to the atmosphere and the ocean, lead to a broad range of complex sea ice dynamics. More in-situ measurements are needed to better identify the phenomena and mechanisms that…
On September 15th 2020, Arctic sea ice extent (SIE) ranked second-to-lowest in history and keeps trending downward. The understanding of how feedback loops amplify the effects of external CO2 forcing is still limited. We propose the…
Decadal climate predictions, which are initialized with observed conditions, are characterized by two main sources of uncertainties--internal and model variabilities. Using an ensemble of climate model simulations from the CMIP5 decadal…
Oxygen isotopes in marine cherts have been used to infer hot oceans during the Archean with temperatures between 60{\deg}C (333 K) and 80{\deg}C (353 K). Such climates are challenging for the early Earth warmed by the faint young Sun. The…
System identification method (SIM) was used to evaluate the Earth equilibrium climate sensitivity. According to our simulations, the equilibrium climate sensitivity was found to be between 2 deg C and 7 deg C. Analysis of the changes in…