Arctic Ocean Freshwater in CMIP6 Coupled Models

In this study we assessed the representation of the sea surface salinity (SSS) and liquid freshwater content (LFWC) of the Arctic Ocean in the historical simulation of 31 CMIP6 models with comparison to 39 Coupled Model Intercomparison Project phase 5 (CMIP5) models, and investigated the projected changes in Arctic liquid and solid freshwater content and freshwater budget in scenarios with two different shared socioeconomic pathways (SSP2-4.5 and SSP5-8.5). No significant improvement was found in the SSS and LFWC simulation from CMIP5 to CMIP6, given the large model spreads in both CMIP phases. The overestimation of LFWC continues to be a common bias in CMIP6. In the historical simulation, the multi-model mean river runoff, net precipitation, Bering Strait and Barents Sea Opening (BSO) freshwater transports are 2,928 ± 1,068, 1,839 ± 3,424, 2,538 ± 1,009, and −636 ± 553 km3/year, respectively. In the last decade of the 21st century, CMIP6 MMM projects these budget terms to rise to 4,346 ± 1,484 km3/year (3,678 ± 1,255 km3/year), 3,866 ± 2,935 km3/year (3,145 ± 2,651 km3/year), 2,631 ± 1,119 km3/year (2,649 ± 1,141 km3/year) and 1,033 ± 1,496 km3/year (449 ± 1,222 km3/year) under SSP5-8.5 (SSP2-4.5). Arctic sea ice is expected to continue declining in the future, and sea ice meltwater flux is likely to decrease to about zero in the mid-21st century under both SSP2-4.5 and SSP5-8.5 scenarios. Liquid freshwater exiting Fram and Davis straits will be higher in the future, and the Fram Strait export will remain larger. The Arctic Ocean is projected to hold a total of 160,300 ± 62,330 km3 (141,590 ± 50,310 km3) liquid freshwater under SSP5-8.5 (SSP2-4.5) by 2100, about 60% (40%) more than its historical climatology

Arctic Ocean Simulations in the CMIP6 Ocean Model Intercomparison Project (OMIP)

oai:publications.copernicus.org:gmdd107357Arctic Ocean simulations in 19 global ocean-sea ice models participating in the Ocean Model Intercomparison Project (OMIP) of the CMIP6 are evaluated in this paper. Our results indicate that no significant improvements were achieved in the Arctic Ocean simulations from the previous Coordinated Ocean-ice Reference Experiments phase II (CORE-II) to the current OMIP. Large model biases and inter-model spread exist in the simulated mean state of the halocline and Atlantic Water layer in the OMIP models. Most of the OMIP models suffer from too thick and deep Atlantic Water layer, too deep halocline base, and large fresh biases in the halocline. The OMIP models largely agree on the inter-annual and decadal variability of the Arctic Ocean freshwater content and volume/heat/freshwater transports through the Arctic Ocean gateways. The models can reproduce observed changes in volume, heat and freshwater transports through the gateways except for the Bering Strait. Overall, the performance of the Arctic Ocean simulations is similar between the CORE2-forced OMIP-1 and JRA55-do-forced OMIP-2.</p

Arctic Ocean Amplification in a warming climate in CMIP6 models

Arctic near-surface air temperature warms much faster than the global average, a phenomenon known as Arctic Amplification. The change of the underlying Arctic Ocean could influence climate through its interaction with sea ice, atmosphere, and the global ocean, but it is less well understood. Here, we show that the upper 2000 m of the Arctic Ocean warms at 2.3 times the global mean rate within this depth range averaged over the 21st century in the Coupled Model Intercomparison Project Phase 6 Shared Socioeconomic Pathway 585 scenario. We call this phenomenon the “Arctic Ocean Amplification.” The amplified Arctic Ocean warming can be attributed to a substantial increase in poleward ocean heat transport, which will continue outweighing sea surface heat loss in the future. Arctic Amplification of both the atmosphere and ocean indicates that the Arctic as a whole is one of Earth’s regions most susceptible to climate change

Future Arctic Climate Change in CMIP6 Strikingly Intensified by NEMO‐Family Climate Models

Climate change in the Arctic has substantial impacts on human life and ecosystems both within and beyond the Arctic. Our analysis of CMIP6 simulations shows that some climate models project much larger Arctic climate change than other models, including changes in sea ice, ocean mixed layer, air-sea heat flux, and surface air temperature in wintertime. In particular, dramatic enhancement of Arctic Ocean convection down to a few hundred meters is projected in these models but not in others. Interestingly, these models employ the same ocean model family (NEMO) while the choice of models for the atmosphere and sea ice varies. The magnitude of Arctic climate change is proportional to the strength of the increase in poleward ocean heat transport, which is considerably higher in this group of models. Establishing the plausibility of this group of models with high Arctic climate sensitivity to anthropogenic forcing is imperative given the implied ramifications

Halo: Estimation and Reduction of Hallucinations in Open-Source Weak Large Language Models

Large Language Models (LLMs) have revolutionized Natural Language Processing (NLP). Although convenient for research and practical applications, open-source LLMs with fewer parameters often suffer from severe hallucinations compared to their larger counterparts. This paper focuses on measuring and reducing hallucinations in BLOOM 7B, a representative of such weaker open-source LLMs that are publicly available for research and commercial applications. We introduce HaloCheck, a lightweight BlackBox knowledge-free framework designed to quantify the severity of hallucinations in LLMs. Additionally, we explore techniques like knowledge injection and teacher-student approaches to alleviate hallucinations in low-parameter LLMs. Our experiments effectively demonstrate the reduction of hallucinations in challenging domains for these LLMs

Dominant inflation of the Arctic Ocean’s Beaufort Gyre in a warming climate

Abstract The Arctic Ocean’s Beaufort Gyre, the largest Arctic freshwater reservoir, plays a crucial role for climate and marine ecosystems. Understanding how it changes in a warming climate is therefore essential. Here, using high-resolution simulations and Coupled Model Intercomparison Project phase 6 data, we find that the Beaufort Gyre will increasingly accumulate freshwater, elevate sea level, and spin up its circulation as the climate warms. These changes, collectively referred to as inflation, are more pronounced in the Beaufort Gyre region than in other Arctic areas, amplifying the spatial asymmetry of the Arctic Ocean. The inflation is driven by increased surface freshwater fluxes and intensified surface stress from wind strengthening and sea ice decline. Current climate models tend to underestimate this inflation, which could be alleviated by high-resolution ocean models and improved atmospheric circulation simulations. The inflation of the Beaufort Gyre underscores its growing importance in a warming climate.</jats:p

LMTuner: An user-friendly and highly-integrable Training Framework for fine-tuning Large Language Models

With the burgeoning development in the realm of large language models (LLMs), the demand for efficient incremental training tailored to specific industries and domains continues to increase. Currently, the predominantly employed frameworks lack modular design, it often takes a lot of coding work to kickstart the training of LLM. To address this, we present "LMTuner", a highly usable, integrable, and scalable system for training LLMs expeditiously and with minimal user-input. LMTuner comprises three main modules - the Interaction, Training, and Inference Modules. We advocate that LMTuner's usability and integrality alleviate the complexities in training large language models. Remarkably, even a novice user could commence training large language models within five minutes. Furthermore, it integrates DeepSpeed frameworks and supports Efficient Fine-Tuning methodologies like Low Rank Adaptation (LoRA), Quantized LoRA (QLoRA), etc., enabling the training of language models scaling from 300M to a whopping 130B parameters using a single server. The LMTuner's homepage (https://wengsyx.github.io/LMTuner/)and screencast video (https://youtu.be/nsXmWOmN3rE) are now publicly available

Comparison of the U37K′, LDI, TEX86H, and RI-OH temperature proxies in sediments from the northern shelf of the South China Sea

The temperature proxies UK′37, LDI, TEXH86, and RI-OH are derived from lipid biomarkers, namely long-chain alkenones from coccolithophorids and long-chain diols ascribed tentatively to eustigmatophytes, as well as glycerol dialkyl glycerol tetraethers (GDGTs) and OH-GDGTs produced by Archaea. The applicability of these proxies in the South China Sea (SCS) has been investigated previously. However, in each study only one or two of the proxies were compared, and the recently updated calibrations or new calibrating methods such as BAYSPAR and BAYSPLINE were not applied. Here, we investigate four proxies in parallel in a set of surface sediment samples from the northern SCS shelf and relate them to local sea surface temperature (SST), which allows for us to compare and assess similarities and differences between them and also help improve regional multiproxy seawater temperature reconstructions. Our results indicate that UK′37 reflects annual mean SST with a slight bias toward the warm season. Terrestrial inputs appear to have a significant impact on LDI, TEXH86, and RI-OH proxies near the coast, leading to colder LDI- and TEXH86-derived temperatures but a warmer RI-OH temperature estimate. After excluding samples influenced by terrestrial materials, we find that LDI-derived temperature agrees well with annual SST, while TEXH86- and RI-OH-derived temperature estimates are close to SSTs in seasons dominated by the East Asian winter monsoon and summer monsoon, respectively. The different seasonal biases of these temperature proxies provide valuable tools to reconstruct regional SSTs under different monsoonal conditions

Distinct Impacts of Increased Atlantic and Pacific Ocean Heat Transport on Arctic Ocean Warming and Sea Ice Decline

Increased ocean heat transport (OHT) to the Arctic Ocean from the Atlantic and Pacific oceans contributes to Arctic Ocean warming and sea ice decline in a warming climate, processes known as Atlantification and Pacification, respectively. However, the separate impacts of these OHTs and their magnitudes remain unclear. This study uses a fully coupled climate model (FIO-ESM v2.1) to investigate the specific impacts of increased Atlantic and Pacific OHTs on Arctic Ocean temperature, sea ice extent, and sea ice concentration. Our sensitivity experiments reveal that increased Atlantic OHT affects the temperature of the entire Arctic Ocean with the greatest impacts found in the Barents Sea and Eurasian Basin and at intermediate depths of the Arctic basin. The warming extent and efficiency from increased Atlantic OHT is considerably greater than that from Pacific OHT. Without warming of the Atlantic Water inflow, the rate of Arctic Ocean warming would decrease by approximately 50%. Increased Pacific OHT mainly affects the upper ocean in the Pacific sector, including the Chukchi Sea, East Siberian Sea, and Canada Basin. Increased OHT from both the Atlantic and Pacific oceans leads to notable sea ice decline with distinct regional and seasonal variations. Increased Atlantic OHT contributes to sea ice decline across most of the Arctic Ocean, particularly in the Barents Sea, the Kara Sea, and the central Arctic. In contrast, increased Pacific OHT leads to sea ice loss dominantly in the Pacific sector, including the Chukchi, the East Siberian, and the Beaufort seas

Arctic Amplification of marine heatwaves under global warming

Marine heatwaves (MHWs) and total heat exposures (THEs), extreme warming events occurring across the global oceans, seriously threaten marine ecosystems and coastal communities as the climate warms. However, future changes in MHWs and THEs in the Arctic Ocean, where unique marine ecosystems are present, are still unclear. Here, based on the latest CMIP6 climate simulations, we find that both MHWs and THEs in the Arctic Ocean are anticipated to intensify in a warming climate, mainly due to Arctic sea ice decline and long-term warming trend, respectively. Particularly striking is the projected rise in MHW mean intensity during the 21st century in the Arctic Ocean, surpassing the global average by more than sevenfold under the CMIP6 SSP585 scenario. This phenomenon, coined the ‘Arctic MHW Amplification’, underscores an impending and disproportionately elevated threat to the Arctic marine life, necessitating targeted conservation and adaptive strategies