Origin and Limits of Invariant Warming Patterns in Climate Models

Выполнена оценка возможных изменений среднегодовой приповерхностной температуры воздуха (ПТВ) в Дальневосточном регионе, включающем территорию и окраинные моря России, а также северо-западную часть Тихого океана, до 2099 г., для чего используются осредненные по ансамблю данные 33 моделей проекта CMIP6 (Coupled Model Intercomparison Project Phase 6), полученные в рамках четырех сценариев, отвечающих разным уровням антропогенного радиационного форсинга (слабого, умеренного и значительного). Анализируются различия между осредненными за 30-летние периоды аномалиями ПТВ. Для верификации модельных результатов проанализировано потепление, произошедшее в регионе с 1940–1969 до 1994–2023 гг., для чего использованы данные реанализа ERA5 и эксперимента Historical CMIP6. По обоим видам данных средняя ПТВ в регионе выросла на 1.1 °С: с 1940–1969 к 1994–2023 гг.; это сходство обосновывает оценки будущих изменений ПТВ по моделям CMIP6. Все сценарии SSP (Shared Socio-economic Pathways) будущего радиационного форсинга показывают приблизительно одинаковое повышение ПТВ с 1994–2023 по 2024–2053 гг., оно составляет в среднем по региону 1.2–1.5 °С. К 2070–2099 гг. средняя ПТВ в рассматриваемом регионе возрастет соответственно темпу эмиссии парниковых газов – на 1.7, 2.7, 3.8 и 4.8 °С. Как показывают данные реанализа ERA5, от 1940–1969 к 1994–2023 гг. увеличение ПТВ над морскими акваториями региона происходило весьма неравномерно: наибольшие темпы наблюдались в северной части Охотского моря (до 2 °С и более) и в прибрежных районах северо-западной части Берингова моря (до 1.0–1.2 °С). Увеличение ПТВ ослабевало в направлении с северо-запада на юго-восток, т.е. с удалением от суши, и составило 0.2–0.6 °С в северо-западной части Тихого океана. Картина потепления над морскими акваториями по данным CMIP6 выражена сильнее, чем по данным реанализа ERA5, но при этом качественно им соответствует. An assessment of possible changes in the annual mean surface air temperature (SAT) in the Far East Region (35°–65° N, 130°–180° E) is made from the present to 2099, using ensemble-averaged data from 33 CMIP6 (Coupled Model Intercomparison Project Phase 6) models obtained within the framework of four scenarios corresponding to the weak, moderate, or significant anthropogenic radiative forcing resulting from СО2 emissions. To elucidate long-term climate change, SAT averaged for 30-year periods, namely, 1994–2023, 2024–2053 and 2070–2099 are analyzed. To verify the model results, the warming that occurred in the region from the mid-20th century (1940–1969) to the early 21st century (1994–2023) is analyzed, using ERA5 data with the fine spatial resolution of 0.25°, and CMIP6 data with the coarser resolution, mostly 1.0°–2.0°. According to both data types, the regional SAT increased, on average by 1.1 °C from 1940–1969 to 1994–2023, justifying the use of forecast estimates based on the CMIP6 models in this work. All scenarios of possible radiative forcing show the similar SAT increase from the 1994–2023 to 2024–2053, on average 1.2–1.5 °C. On the contrary, by the 2070–2099, the regional SAT will increase in accordance with the emission rates on average by 1.7, 2.7, 3.8 and 4.8 °C, respectively. As for the Russian Far East land area, ERA5 and CMIP6 show similar spatial warming patterns, with the warming, on average, of 1.2 °C from 1940–1969 to 1994–2023, i.e. higher than that for the entire considered region including marine areas. From 1940–1969 to 1994–2023 negative annual mean SAT changed to positive one in some areas of the Primorsky, Khabarovsky and Kamchatksky provinces, implying the permafrost melting. According to the CMIP6 models, the land warming of 2.0–2.1 °C, 3.0–3.5 °C, 4.7–5.3 °C, and 6.1–6.6 °C is expected by the end of the 21st century for the scenarios with the different levels of radiative forcing. As shown by the ERA5 data, the SAT increase from 1940–1969 to 1994–2023 was very uneven for the marine areas: the highest rates were observed in the northern Okhotsk Sea (up to 2 °C and more) and in the coastal northwestern Bering Sea (up to 1.0–1.2 °C), which can be explained by the ice cover decrease. The SAT increase weakened in the direction from the northwest to southeast, i.e. with the distance from the land, and amounted to only 0.2–0.6 °C in the northwestern Pacific, which can be attributed to the effect of Pacific Decadal Oscillation (PDO). The coastal Okhotsk Sea off the Sakhalin Island is the only area where SAT decreased by 0.2–0.6 °C from 1940–1969 to 1994–2023, which probably can be attributed to the changes in the East Sakhalin Current transporting Amur River water southward along the coast but this suggestion should be verified. The warming pattern over the marine areas according to CMIP6 data qualitatively corresponds to that one based on ERA5 data, keeping in mind the lower resolution of the modeled data. The warming in the Northwest Pacific from the modeled data exceeds that one from ERA5, which can be explained by elimination of the PDO effects when averaging CMIP6 multi-model data.

Horizontal temperature gradients in the tropical free troposphere are fairly weak, and tropical tropospheric warming is usually treated as uniform. However, we show here that projected tropospheric warming is spatially inhomogeneous in Coupled Model Intercomparison Project Phase 6 models, as well as in a storm‐resolving climate model. We relate the upper tropospheric warming pattern to sea‐surface temperature changes that reorganise convection and thereby cause spatial shifts in convective heating. Using the classical Gill model for tropical circulation and forcing it with precipitation changes that arise due to greenhouse gas warming, we can understand and reproduce the different warming patterns simulated by a range of global climate models. Forcing the Gill model with precipitation changes from a certain region demonstrates how local tropospheric temperature changes depend on local changes in convective heating. Close to the Equator, anomalous geopotential gradients are balanced by the dissipation term in the Gill model. The optimal dissipation time‐scale to reproduce the warming pattern varies depending on the Coupled Model Intercomparison Project Phase 6 model, and is between 1 and 10 days. We demonstrate that horizontal advection and eddy momentum fluxes have large enough equivalent dissipation time‐scales to balance the gradients in geopotential and thereby shape the warming pattern. Though climate models show a large spread in projections of tropical sea‐surface temperature and precipitation changes, our results imply that, once these predictions improve, our confidence in the predicted upper tropospheric warming pattern should also increase.

The Tibetan Plateau snow cover exhibits notable subseasonal variability and plays a crucial role in influencing the atmosphere. This study employs numerical experiments to investigate the atmospheric feedback resulting from extreme anomalous snow cover events on the Tibetan Plateau, with a focus on both local and nonlocal atmospheric temperatures. The findings reveal that diabatic heating, directly induced by these events, leads to a local surface energy cooling response over the Tibetan Plateau, contributing to a reduction in local temperatures. This cooling effect amplifies local atmospheric temperature anomalies associated with extreme anomalous Tibetan Plateau snow cover events, constituting approximately 50% of the total final local surface air temperature anomalies. Furthermore, the Tibetan Plateau snow cover, through adiabatic processes, exerts a nonlocal influence on atmospheric temperature and circulation. The atmospheric temperature responses downstream of the Tibetan Plateau vary at different heights and regions, featuring both cold and warm anomaly responses. These variations depend on the relative contributions of horizontal advection and vertical advection in adiabatic heating. Significance Statement Snow cover is influenced by the atmosphere, and in turn, it affects the atmosphere. This study examines the feedback of extreme anomalous Tibetan Plateau snow cover events on the atmosphere at the subseasonal time scale, with a focus on atmospheric temperature. Our findings indicate that Tibetan Plateau snow cover has both local and nonlocal feedback effects on the atmosphere. In particular, extreme anomalous Tibetan Plateau snow cover amplifies local surface air temperature anomalies. The feedback contributes to approximately 50% of the total final local surface air temperature anomalies.

Cold winters in Eurasia considerably affect transportation, agriculture, energy, and public health. This study utilizes 31 global climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and 33 CMIP5 models to evaluate the historical surface air temperature, sea level pressure, 500‐hPa geopotential height, 150‐hPa meridional and zonal wind, and polar vortex indices during cold winters. Our research quantifies the advancements of CMIP6 over CMIP5. Additionally, future changes in these variables under three different Shared Socioeconomic Pathways (SSPs), that is, SSP 1–2.6, SSP 2–4.5, and SSP 5–8.5, are projected based on 20 out of the 31 CMIP6 models. The results indicate that the multimodel ensemble means from both CMIP5 and CMIP6 effectively capture the main features of the observed Eurasian cold winters and their associated factors with good simulation agreement. The CMIP6 ensemble mean outperforms its CMIP5 counterpart, and both ensemble means (CMIP5 and CMIP6) perform better than individual CMIP6 models. Among CMIP6 models, 500‐hPa geopotential height achieves the highest simulation skill, whereas sea level pressure shows the lowest. Compared with same‐institute models from CMIP5, CMIP6 models show overall improvements with sea level pressure simulation being notably advanced. Under the three SSPs, the occurrence probability of cold winters is projected to decrease as the area and intensity indices of the polar vortex decline. Moreover, surface temperature anomalies are projected to exhibit a “warm Arctic and cold Eurasia” pattern, and the anticyclonic anomalies at 500 hPa and 150 hPa are projected to be centered at high latitudes.

The characteristics and causes of inhomogeneous warming of the Tropical Indian Ocean (TIO) sea surface temperature during 1900–2005 are investigated based on observations and 16 Coupled Model Intercomparison Project phase 5 (CMIP5) models. Over the TIO, the observed warming trend has more than doubled since 1965, which is well simulated by the CMIP5 historical runs. However, as to spatial warming pattern, observations manifest a double-peak pattern during 1900–1940 and a non-uniform Indian Ocean Mode (IOBM)-like pattern during 1965–2005, which is not captured by the CMIP5 historical runs. Herein, an optimal detection analysis is employed, which indicates that the double-peak warming pattern can be explained well by a combination of Greenhouse Gas (GHG) and natural forcing, and the non-uniform IOBM-like pattern is mostly attributable to anthropogenic forcing. Further, a mixed-layer heat budget analysis shows that atmospheric and oceanic processes, especially latent heat flux from atmospheric forcing part associated with GHG forcing, are beneficial for the warming patterns formation. Our study supports the claim that intrinsic ocean–atmosphere interaction within the TIO is the key mechanism for maintaining the TIO warming. From the model perspective, during 1900–1940, the weak anti-symmetric atmospheric circulation with easterly (northwesterly) anomalies north (south) of the equator helps to sustain the double-peak warming pattern. During 1965–2005, the intensified anti-symmetric wind pattern is in favor of the non-uniform IOBM-like warming pattern.

In this study, we analyzed temperature, Multivariate El Niño-Southern Oscillation Index (MEI), and Standard Precipitation Index (SPI) data from the San Francisco Bay Area from 1971 to 2016. We also analyzed CO2 records from Mauna Loa, HI for the same time period, along with the annual temperature anomalies for the Bay Area. Understanding the relationships between temperature, MEI, SPI, and CO2 concentration is important as they measure the major influencers of California’s regional climate: temperature, ENSO, precipitation, and atmospheric CO2. Thus, measurements of the three variables are key indicators of long term trends in climate, and can reveal the exact effect anthropogenic climate change is having on the Bay Area’s climate. Our research question was whether there is a correlation between temperature, MEI, SPI, and atmospheric CO2 within the Bay Area. We found that there was a clear correlation between warm anomalies and high MEI/low SPI in the period of 2013–2016, however only when both were historically significant. Also, MEI levels in general were highly correlated with temperature, showing that the local temperature anomalies in the Bay Area are significantly influenced by the El Niño-Southern Oscillation (ENSO) cycle. The influence of precipitation on the local temperature anomalies was limited, however. Finally, although there was not a statistically significant link between the atmospheric CO2 concentration at Mauna Loa, HI and the temperature anomalies in the Bay Area, the consistent increase in CO2 concentration could have had an impact on the overall increase in annual temperature anomalies from 1971 to 2016.

Abstract. The Greenland Ice Sheet (GrIS) has been losing mass since the 1990s as a direct consequence of rising temperatures and has been projected to continue to lose mass at an accelerating pace throughout the 21st century, making it one of the largest contributors to future sea-level rise. The latest Coupled Model Intercomparison Project Phase 6 (CMIP6) models produce a greater Arctic amplification signal and therefore also a notably larger mass loss from the GrIS when compared to the older CMIP5 projections, despite similar forcing levels from greenhouse gas emissions. However, it is also argued that the strength of regional factors, such as melt–albedo feedbacks and cloud-related feedbacks, will partly impact future melt and sea-level rise contribution, yet little is known about the role of these regional factors in producing differences in GrIS surface melt projections between CMIP6 and CMIP5. In this study, we use high-resolution (15 km) regional climate model simulations over the GrIS performed using the Modèle Atmosphérique Régional (MAR) to physically downscale six CMIP5 Representative Concentration Pathway (RCP) 8.5 and five CMIP6 Shared Socioeconomic Pathway (SSP) 5-8.5 extreme high-emission-scenario simulations. Here, we show a greater annual mass loss from the GrIS at the end of the 21st century but also for a given temperature increase over the GrIS, when comparing CMIP6 to CMIP5. We find a greater sensitivity of Greenland surface mass loss in CMIP6 centred around summer and autumn, yet the difference in mass loss is the largest during autumn with a reduction of 27.7 ± 9.5 Gt per season for a regional warming of +6.7 ∘C and 24.6 Gt per season more mass loss than in CMIP5 RCP8.5 simulations for the same warming. Assessment of the surface energy budget and cloud-related feedbacks suggests a reduction in high clouds during summer and autumn – despite enhanced cloud optical depth during autumn – to be the main driver of the additional energy reaching the surface, subsequently leading to enhanced surface melt and mass loss in CMIP6 compared to CMIP5. Our analysis highlights that Greenland is losing more mass in CMIP6 due to two factors: (1) a (known) greater sensitivity to greenhouse gas emissions and therefore warmer temperatures and (2) previously unnotified cloud-related surface energy budget changes that enhance the GrIS sensitivity to warming.

Abstract. Anthropogenic climate change is projected to lead to ocean warming, acidification, deoxygenation, reductions in near-surface nutrients, and changes to primary production, all of which are expected to affect marine ecosystems. Here we assess projections of these drivers of environmental change over the twenty-first century from Earth system models (ESMs) participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) that were forced under the CMIP6 Shared Socioeconomic Pathways (SSPs). Projections are compared to those from the previous generation (CMIP5) forced under the Representative Concentration Pathways (RCPs). A total of 10 CMIP5 and 13 CMIP6 models are used in the two multi-model ensembles. Under the high-emission scenario SSP5-8.5, the multi-model global mean change (2080–2099 mean values relative to 1870–1899) ± the inter-model SD in sea surface temperature, surface pH, subsurface (100–600 m) oxygen concentration, euphotic (0–100 m) nitrate concentration, and depth-integrated primary production is +3.47±0.78 ∘C, -0.44±0.005, -13.27±5.28, -1.06±0.45 mmol m−3 and -2.99±9.11 %, respectively. Under the low-emission, high-mitigation scenario SSP1-2.6, the corresponding global changes are +1.42±0.32 ∘C, -0.16±0.002, -6.36±2.92, -0.52±0.23 mmol m−3, and -0.56±4.12 %. Projected exposure of the marine ecosystem to these drivers of ocean change depends largely on the extent of future emissions, consistent with previous studies. The ESMs in CMIP6 generally project greater warming, acidification, deoxygenation, and nitrate reductions but lesser primary production declines than those from CMIP5 under comparable radiative forcing. The increased projected ocean warming results from a general increase in the climate sensitivity of CMIP6 models relative to those of CMIP5. This enhanced warming increases upper-ocean stratification in CMIP6 projections, which contributes to greater reductions in upper-ocean nitrate and subsurface oxygen ventilation. The greater surface acidification in CMIP6 is primarily a consequence of the SSPs having higher associated atmospheric CO2 concentrations than their RCP analogues for the same radiative forcing. We find no consistent reduction in inter-model uncertainties, and even an increase in net primary production inter-model uncertainties in CMIP6, as compared to CMIP5.

CR Climate Research Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsSpecials CR 25:171-178 (2003) - doi:10.3354/cr025171 Influence of El Niño/southern oscillation, Pacific decadal oscillation, and local sea-surface temperature anomalies on peak season monsoon precipitation in India Shouraseni Sen Roy, Gregory B. Goodrich, Robert C. Balling Jr* Department of Geography, Arizona State University, Tempe, Arizona 85287, USA *Corresponding author. Email: robert.balling@asu.edu ABSTRACT: Many modeling and empirical studies have revealed that summer monsoon precipitation in India is significantly affected by El Niño/Southern Oscillation (ENSO) as well as by sea-surface temperatures (SSTs) in the Arabian Sea, Bay of Bengal, and Indian Ocean. Recently, the impact of the Pacific decadal oscillation (PDO) on Indian rainfall has been the focus of research. In this investigation, we collect monthly rainfall data for 18 grid cells covering India and develop statistical indices of ENSO, PDO, and local SSTs over the period 1925-1998. We find that ENSO reduces precipitation in southern India while having a small impact over most of the country. The PDO appears to amplify the ENSO signal in southern India, while local SSTs were directly related to monsoon precipitation totals in the southern peninsula region. While the associations are often statistically significant, the combination of ENSO, PDO, and SSTs explains less than 20% of the variance in monsoon rainfall throughout India. KEY WORDS: India monsoon rainfall · El Niño/Southern Oscillation · Pacific Decadal Oscillation · Sea surface temperatures Full text in pdf format PreviousNextExport citation RSS - Facebook - Tweet - linkedIn Cited by Published in CR Vol. 25, No. 2. Online publication date: December 05, 2003 Print ISSN: 0936-577X; Online ISSN: 1616-1572 Copyright © 2003 Inter-Research.

Climate change can pose a significant threat to water fluxes on terrestrial surfaces, impacting water availability, and increasing the risk for human-environment systems to floods and droughts. Understanding the repercussions of climate change on future water resources is imperative for effective integrated water resources management. As part of the DISTENDER project (EU Horizon-ID 101056836), we scrutinize the effects of climate change on diverse watersheds in Europe to develop strategies for climate change adaptation.To simulate the impacts of climate change on water resources, we chose MIKE SHE for its spatially distributed and physically based modeling concept. Here we present the results of different climate models vs. SSPs on water balance components and runoff for the Ave River Basin in Northern Portugal.  MIKE SHE was calibrated and validated utilizing measured gauge runoff data from 1980 to 1986 and 1986 to 1990, respectively. For the various gauges, Nash-Sutcliffe efficiencies between 0.59 and 0.81 were achieved.Statistically downscaled climate change projections for the period (2021-2050) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) were used as input to MIKE SHE. We used three different climate models (CanESM5, EC-EARTH3, MPI-ESM1-2-HR) and four shared socioeconomic pathways (SSPs 1-2.6, 2-4.5, 3-7.0, 5-8.5) each. Hydrological variables were evaluated for each of the twelve-climate model runs in comparison to the reference period (1980-2010).  All climate simulations show an increase in annual precipitation, except for CanESM5 SSP 3-7.0, MPI-ESM1-2-HR SSP 2-4.5, and MPI-ESM1-2-HR SSP 3-7.0. The precipitation increases range from 1 % to 24 %. This underscores the impacts of different SSPs and climate models on projected regional precipitation patterns and emphasizes their importance in comprehensive climate change assessments. In all scenarios, the projections indicate an increase in flood for different durations (1-day, 3-days) at all gauges across different return periods. The flood increase calculated for the three different climate models exhibits greater differences than the flood increase calculated for different SSPs across climate models. For example, in the Ave River, the range of the 100-year flood across SSPs varies from 81 m³/s (Min: 432m³/s, Max: 513 m³/s) for MPI-ESM1-2-HR to 225 m³/s (Min: 496 m³/s, Max: 721 m³/s) for EC-EARTH3. The corresponding range across models spans from 71 m³/s (Min: 425 m³/s, Max: 496 m³/s) for SSPs 3-7.0 to 213 m³/s (Min: 508 m³/s, Max: 721 m³/s) for SSPs 5-8.5. The 100-year flood (1-day duration) in the reference period value is 372 m³/s. In addition, the duration of low-flow events increases significantly for most climate scenarios. This increase in extreme events, which includes both, an increase in the volume of floods and an increase in the duration of droughts, emphasizes the need for proactive measures to address and adapt to the anticipated changes in hydrological patterns due to climate change.However, our findings show that the selection of the climate model has a great impact on the hydrological variables. Decision-makers should carefully choose a climate model aligned with their planning objectives, considering the potential risk for robust planning.Keywords: Climate change, CIMP6 Climate Model, MIKE-SHE, Ave catchment 

Local temperature anomalies increase climate policy interest and support: Analysis of internet searches and US congressional vote shares

This paper presents the changes in projected temperature and precipitation over the Arabian Peninsula for the twenty-first century using the Coupled Model Intercomparison Project phase 6 (CMIP6) dataset. The changes are obtained by analyzing the multimodel ensemble from 31 CMIP6 models for the near (2030–2059) and far (2070–2099) future periods, with reference to the base period 1981–2010, under three future Shared Socioeconomic Pathways (SSPs). Observations show that the annual temperature is rising at the rate of 0.63 ˚C decade–1 (significant at the 99% confidence level), while annual precipitation is decreasing at the rate of 6.3 mm decade–1 (significant at the 90% confidence level), averaged over Saudi Arabia. For the near (far) future period, the 66% likely ranges of annual-averaged temperature is projected to increase by 1.2–1.9 (1.2–2.1) ˚C, 1.4–2.1 (2.3–3.4) ˚C, and 1.8–2.7 (4.1–5.8) ˚C under SSP1–2.6, SSP2–4.5, and SSP5–8.5, respectively. Higher warming is projected in the summer than in the winter, while the Northern Arabian Peninsula (NAP) is projected to warm more than Southern Arabian Peninsula (SAP), by the end of the twenty-first century. For precipitation, a dipole-like pattern is found, with a robust increase in annual mean precipitation over the SAP, and a decrease over the NAP. The 66% likely ranges of annual-averaged precipitation over the whole Arabian Peninsula is projected to change by 5 to 28 (–3 to 29) %, 5 to 31 (4 to 49) %, and 1 to 38 (12 to 107) % under SSP1–2.6, SSP2–4.5, and SSP5–8.5, respectively, in the near (far) future. Overall, the full ranges in CMIP6 remain higher than the CMIP5 models, which points towards a higher climate sensitivity of some of the CMIP6 climate models to greenhouse gas (GHG) emissions as compared to the CMIP5. The CMIP6 dataset confirmed previous findings of changes in future climate over the Arabian Peninsula based on CMIP3 and CMIP5 datasets. The results presented in this study will be useful for impact studies, and ultimately in devising future policies for adaptation in the region.

Abstract. Overshoot scenarios, in which the forcing reaches a peak before starting to decline, show non-symmetric changes during CO2-increasing and CO2-decreasing phases, producing persistent changes in climate. Irreversibility mechanisms, associated with (among other factors) lagged responses of climate components, changes in ocean circulation and heat transport, and changes in the ice cover, bring hysteresis to the climate system. This work analyzes simulations from the Coupled Model Intercomparison Project Phase 6 (CMIP6) to explore the relevance of these mechanisms in overshoot scenarios with different forcing conditions (SSP5-3.4OS and SSP1-1.9) and their impact on regional climates, with a particular focus on the degree to which changes in regional extremes are reversible. These analyses show that in scenarios with strong forcing changes like SSP5-3.4OS, the post-overshoot state is characterized by a temperature asymmetry between the Northern Hemisphere and Southern Hemisphere associated with shifts in the Intertropical Convergence Zone (ITCZ). In scenarios with lower forcing changes like SSP1-1.9, this hemispheric asymmetry is more limited, while temperature changes in polar areas are more prominent. These large-scale changes have an impact on regional climates, e.g., temperature extremes in extratropical regions and precipitation extremes in tropical regions around the ITCZ. Differences between pre- and post-overshoot states may be associated with persistent changes in the heat transport and a different thermal inertia depending on the region, leading to a different timing of the temperature maximum in different regions. Other factors like changes in aerosol emissions and ice melting may be also important, particularly for polar areas. Results show that irreversibility of temperature and precipitation extremes is mainly caused by the transitions around the global temperature maximum, when a decoupling between regional extremes and global temperature generates persistent changes at regional level.

Environmental temperature is a widely used variable to describe weather and climate conditions. The use of temperature anomalies to identify variations in climate and weather systems makes temperature a key variable to evaluate not only climate variability but also shifts in ecosystem structural and functional properties. In contrast to terrestrial ecosystems, the assessment of regional temperature anomalies in coastal wetlands is more complex since the local temperature is modulated by hydrology and weather. Thus, it is unknown how the regional free-air temperature (TFree) is coupled to local temperature anomalies, which can vary across interfaces among vegetation canopy, water, and soil that modify the wetland microclimate regime. Here, we investigated the temperature differences (offsets) at those three interfaces in mangrove-saltmarsh ecotones in coastal Louisiana and South Florida in the northern Gulf of Mexico (2017–2019). We found that the canopy offset (range: 0.2–1.6°C) between TFree and below-canopy temperature (TCanopy) was caused by the canopy buffering effect. The similar offset values in both Louisiana and Florida underscore the role of vegetation in regulating near-ground energy fluxes. Overall, the inundation depth did not influence soil temperature (TSoil). The interaction between frequency and duration of inundation, however, significantly modulated TSoil given the presence of water on the wetland soil surface, thus attenuating any short- or long-term changes in the TCanopy and TFree. Extreme weather events—including cold fronts and tropical cyclones—induced high defoliation and weakened canopy buffering, resulting in long-term changes in canopy or soil offsets. These results highlight the need to measure simultaneously the interaction between ecological and climatic processes to reduce uncertainty when modeling macro- and microclimate in coastal areas under a changing climate, especially given the current local temperature anomalies data scarcity. This work advances the coupling of Earth system models to climate models to forecast regional and global climate change and variability along coastal areas.

The authors examine the net winter, summer, and annual mass balance of six glaciers along the northwest coast of North America, extending from Washington State to Alaska. The net winter (NWB) and net annual (NAB) mass balance anomalies for the maritime glaciers in the southern group, located in Washington and British Columbia, are shown to be positively correlated with local precipitation anomalies and storminess (defined as the rms of high-passed 500-mb geopotential anomalies) and weakly and negatively correlated with local temperature anomalies. The NWB and NAB of the maritime Wolverine glacier in Alaska are also positively correlated with local precipitation, but they are positively correlated with local winter temperature and negatively correlated with local storminess. Hence, anomalies in mass balance at Wolverine result mainly from the change in moisture that is being advected into the region by anomalies in the averaged wintertime circulation rather than from a change in storminess. The patterns of the wintertime 500-mb circulation and storminess anomalies associated with years of high NWB in the southern glacier group are similar to those associated with low NWB years at the Wolverine glacier, and vice versa. The decadal ENSO-like climate phenomenon discussed by Zhang et al. has a large impact on the NWB and NAB of these maritime glaciers, accounting for up to 35% of the variance in NWB. The 500-mb circulation and storminess anomalies associated with this decadal ENSO-like mode resemble the Pacific–North American pattern, as do 500-mb composites of years of extreme NWB of South Cascade glacier in Washington and of Wolverine glacier in Alaska. Hence, the decadal ENSO-like mode affects precipitation in a crucial way for the NWB of these glaciers. Specifically, the decadal ENSO-like phenomenon strongly affects the storminess over British Columbia and Washington and the moisture transported by the seasonally averaged circulation into maritime Alaska. In contrast, ENSO is only weakly related to NWB of these glaciers because (i) the large-scale circulation anomalies associated with ENSO do not produce substantial anomalies in moisture advection into Alaska, and (ii) the storminess and precipitation anomalies associated with ENSO are far to the south of the southern glacier group. Finally, the authors discuss the potential for short-term climate forecasts of the mass balance for the maritime glaciers in the northwest of North America.