Although adequately detailed kerosene chemical-combustion Arrhenius reaction-rate suites were not readily available for combustion modeling until ca. the 1990’s (e.g., Marinov [1998]), it was already known from mass-spectrometer measurements during the early Apollo era that fuel-rich liquid oxygen + kerosene (RP-1) gas generators yield large quantities (e.g., several percent of total fuel flows) of complex hydrocarbons such as benzene, butadiene, toluene, anthracene, fluoranthene, etc. (Thompson [1966]), which are formed concomitantly with soot (Pugmire [2001]). By the 1960’s, virtually every fuel-oxidizer combination for liquid-fueled rocket engines had been tested, and the impact of gas phase combustion-efficiency governing the rocket-nozzle efficiency factor had been empirically well-determined (Clark [1972]). Up until relatively recently, spacelaunch and orbital-transfer engines were increasingly designed for high efficiency, to maximize orbital parameters while minimizing fuels and structural masses: Preburners and high-energy atomization have been used to pre-gasify fuels to increase (gas-phase) combustion efficiency, decreasing the yield of complex/aromatic hydrocarbons (which limit rocket-nozzle efficiency and overall engine efficiency) in hydrocarbon-fueled engine exhausts, thereby maximizing system launch and orbital-maneuver capability (Clark; Sutton; Sutton/Yang). The combustion community has been aware that the choice of Arrhenius reaction-rate suite is critical to computer engine-model outputs. Specific combustion suites are required to estimate the yield of high-molecular-weight/reactive/toxic hydrocarbons in the rocket engine combustion chamber, nonetheless such GIGO errors can be seen in recent documents. Low-efficiency launch vehicles also need larger fuels loads to achieve the same launched mass, further increasing the yield of complex hydrocarbons and radicals deposited by low-efficiency rocket engines along launch trajectories and into the stratospheric ozone layer, the mesosphere, and above. With increasing launch rates from low-efficiency systems, these persistent (Ross/Sheaffer [2014]; Sheaffer [2016]), reactive chemical species must have a growing impact on critical, poorly-understood upper-atmosphere chemistry systems.

Although adequately detailed kerosene chemical-combustion Arrhenius reaction-rate suites were not readily available for combustion modeling until ca. the 1990’s (e.g., Marinov [1998]), it was already known from mass-spectrometer measurements during the early Apollo era that fuel-rich liquid oxygen + kerosene (RP-1) gas generators yield large quantities (e.g., several percent of total fuel flows) of complex hydrocarbons such as benzene, butadiene, toluene, anthracene, fluoranthene, etc. (Thompson [1966]), which are formed concomitantly with soot (Pugmire [2001]). By the 1960’s, virtually every fuel-oxidizer combination for liquid-fueled rocket engines had been tested, and the impact of gas phase combustion-efficiency governing the rocket-nozzle efficiency factor had been empirically well-determined (Clark [1972]). Up until relatively recently, spacelaunch and orbital-transfer engines were increasingly designed for high efficiency, to maximize orbital parameters while minimizing fuels and structural masses: Preburners and high-energy atomization have been used to pre-gasify fuels to increase (gas-phase) combustion efficiency, decreasing the yield of complex/aromatic hydrocarbons (which limit rocket-nozzle efficiency and overall engine efficiency) in hydrocarbon-fueled engine exhausts, thereby maximizing system launch and orbital-maneuver capability (Clark; Sutton; Sutton/Yang). The rocket combustion community has been aware that the choice of Arrhenius reaction-rate suite is critical to computer engine-model outputs. Specific combustion suites are required to estimate the yield of high-molecular-weight/reactive/toxic hydrocarbons in the rocket engine combustion chamber, nonetheless such GIGO errors can be seen in recent documents. Low-efficiency launch vehicles (SpaceX, Hanwha) therefore also need larger fuels loads to achieve the same launched/transferred mass, further increasing the yield of complex hydrocarbons and radicals deposited by low-efficiency rocket engines along launch trajectories and into the stratospheric ozone layer, the mesosphere, and above. With increasing launch rates from low-efficiency systems, these persistent (Ross/Sheaffer [2014]; Sheaffer [2016]), reactive chemical species must have a growing impact on critical, poorly-understood upper-atmosphere chemistry systems.

Many regions across the globe broke their surface temperature records in recent years, further sparking concerns about the impending arrival of “tipping points” later in the 21st century. This study analyzes observed global surface temperature trends in three target latitudinal regions: the Arctic Circle, the Tropics, and the Antarctic Circle. We show that global warming is accelerating unevenly across the planet, with the Arctic warming at approximately three times the average rate of our world. We further analyzed the reliability of latitude-dependent surface temperature simulations from a suite of Coupled Model Intercomparison Project Phase 6 models and their multi-model mean. We found that GISS-E2-1-G and FGOALS-g3 were the best-performing models based on their statistical abilities to reproduce observational, latitude-dependent data. Surface temperatures were projected from ensemble simulations of the Shared Socioeconomic Pathway 2-4.5 (SSP2-4.5). We estimate when the climate will warm by 1.5, 2.0, and 2.5 ℃ relative to the preindustrial period, globally and regionally. GISS-E2-1-G projects that global surface temperature anomalies would reach 1.5, 2.0, and 2.5 ℃ in 2024 (±1.34), 2039 (±2.83), and 2057 (±5.03) respectively, while FGOALS-g3 predicts these “tipping points” would arrive in 2024 (±2.50), 2054 (±7.90), and 2087 (±10.55) respectively. Our results reaffirm a dramatic, upward trend in projected climate warming acceleration, with upward concavity in 21st century projections of the Arctic, which could lead to catastrophic consequences across the Earth. Further studies are necessary to determine the most efficient solutions to reduce global warming acceleration and maintain a low SSP, both globally and regionally.

Weighting models according to their performance has been used in constructing multi-model regional climate change scenarios. But the added value of model weighting is not always examined. Here we apply an imperfect model framework to examine the added value of model weighting in projecting summer temperature changes over China. Members of large ensemble initial condition simulations by three climate models of different climate sensitivities under the historical forcing and future scenarios are used as pseudo-observations. Performance of the models participating in the 6th phase of the coupled model intercomparison project (CMIP6) in simulating past climate are evaluated against the pseudo-observations based on climatology, trends in global, regional and local temperatures. The performance along with model’s independence are used to determine the model weights for future projection. The weighted projections are then compared with the pseudo-observations for the future. We find that regional trend as a metric of model performance yields the best skill for future projection while past climatology as performance metric does not improve future projection. Trend at the grid-box scale is also not a good performance indicator as small scale trend is highly uncertain. Projected summer warming based on model weighting is similar to that of unweighted projection, at 2.3°C increase relative to 1995-2014 by the middle of the 21st century under SSP8.5 scenario, but the 5th-95th uncertainty range of the weighted projection is 18% smaller with the reduction mainly in the upper bound, with the largest reduction in the northern Tibetan Plateau.

Warm, salty Circumpolar Deep Water (CDW) is recognized as the primary driver for Antarctic glacial melt, but the mechanism by which it reaches the continental shelves remains highly uncertain from an observational standpoint. With the scarcity of eddy flux estimation in the Antarctic margin, we quantify the isopycnal diffusivity of CDW using hydrographic variability and satellite altimetry under the mixing length framework. For comparison, the spiciness and thickness are used as isopycnal tracers, and the two tracers yield qualitatively similar estimates. Over the Antarctic Circumpolar Current (ACC), spatial variation of mixing length is generally aligned with the jet-induced mixing suppression theory, including its exception in the lee of the topography. In contrast, the mixing length does not depend on the mean flow in the subpolar zone, likely reflecting the relatively quiescent flow regime. The estimated isopycnal diffusivity ranges from 100 to 500 m2 s-1 south of the ACC. The eddy diffusivity tends to be enhanced where the gradient of isopycnal thickness becomes small and CDW intrudes onshore. The cross-slope eddy CDW flux is estimated, and the associated onshore heat flux across is calculated as ~3.6 TW in the eastern Indian sector. The eddy heat flux and coastal solar heating are generally balanced with cryospheric heat sinks including glacial melting and surface freezing, suggesting that the eddy advection is substantial for the onshore CDW flux. The thickness field is essential for determining mixing length and eddy fluxes in the subpolar zone, whereas the situation does not hold for the ACC domain.

The El Niño-Southern Oscillation (ENSO) in the equatorial Pacific is the dominant mode of global air-sea CO2 flux interannual variability (IAV). Air-sea CO2 fluxes are driven by the difference between atmospheric and surface ocean pCO2, with variability of the latter driving flux variability. Previous studies found that models in Coupled Model Intercomparison Project Phase 5 (CMIP5) failed to reproduce the observed ENSO-related pattern of CO2 fluxes and had weak pCO2 IAV, which were explained by both weak upwelling IAV and weak mean vertical DIC gradients. We assess whether the latest generation of CMIP6 models can reproduce equatorial Pacific pCO2 IAV by validating models against observations-based data products. We decompose pCO2 IAV into thermally and non-thermally driven anomalies to examine the balance between these competing anomalies, which explain the total pCO2 IAV. The majority of CMIP6 models underestimate pCO2 IAV, while they overestimate SST IAV. Thermal and non-thermal pCO2 anomalies are not appropriately balanced in models, such that the resulting pCO2 IAV is too weak. We compare the relative strengths of the vertical transport of temperature and DIC and evaluate their contributions to thermal and non-thermal pCO2 anomalies. Model-to-observations-based product comparisons reveal that modeled mean vertical DIC gradients are biased weak relative to their mean vertical temperature gradients, but upwelling acting on these gradients is insufficient to explain the relative magnitudes of thermal and non-thermal pCO2 anomalies.

The Central Highlands of Vietnam is the biggest Robusta coffee (Coffea canephora Pierre ex A.Froehner) growing region in the world. This study aims to identify the most important climatic variables that determine the current distribution of coffee in the Central Highlands and build a “coffee suitability” model to assess changes in this distribution due to climate change scenarios. A suitability model based on neural networks was trained on coffee occurrence data derived from national statistics on coffee-growing areas. Bias-corrected regional climate models were used for two climate change scenarios (RCP8.5 and RCP2.6) to assess changes in suitability for three future time periods (i.e., 2038-2048, 2059-2069, 2060-2070) relative to the 2009-2019 baseline. Average expected losses in suitable areas were 62% and 27% for RCP8.5 and RCP2.6, respectively. The loss in suitability due to RCP8.5 is particularly pronounced after 2060. Increasing mean minimum temperature during harvest (October-November) and growing season (March-September) and decreasing precipitation during late growing season (July-September) mainly determined the loss in suitable areas. If the policy commitments made at the Paris agreement are met, the loss in coffee suitability could potentially be compensated by climate change adaptation measures such as making use of shade trees and adapted clones.

Extreme heat waves beset western North America during 2021, including a 46.7°C (116°F) observation in Portland, Oregon, an astonishing 5°C above the previous record. Using Portland as an example we provide evidence for a latent risk of extreme heat waves in the Pacific Northwest (PNW) and along the west coast of the United States where a maritime climate and its intrinsic variations yield a positive skewness in summertime daily maximum temperatures. A generalized Pareto extreme value analysis yields a heavy tailed distribution with a return period of 300-1000 years, indicating that, while rare, the event was possible, contrary to prior claims that the event was “virtually impossible”. We demonstrate that the extreme temperatures can be explained by the coincident extreme values of geopotential heights, and that the relationship between heights and extreme temperatures has not materially changed over the observational record. The dynamical nature of the event along with recent developments in stochastic theory justifies the use of skewed and heavy-tailed distributions which may provide the basis for a more proactive approach to managing the risk of future events.

Heatwaves occurred frequently in summers, severely harming natural environment and human society. While a few long-term spatiotemporal heatwave studies have been conducted in China at the grid scale, their shortcomings involve discrete distribution and poor spatiotemporal continuity. We used daily data of 691 meteorological stations to obtain torridity index (TI) and heatwave index (HWI) datasets (0.01°), to evaluate the spatiotemporal distribution of heatwaves in Chinese mainland for 1990-2019. The results were as follows: (1) TI rose but with fluctuations. The largest increase occurred in North China in July. Areas with hazard levels of medium and above accounted for 22.16%, mainly in the eastern and southern provinces of China, South Tibet, East and South Xinjiang, and Chongqing. The hazard indicators in Chongqing and central Zhejiang were at especially high levels, which is concerning. (2) Average heatwave frequency, intensity, and duration reached relatively high levels of 6-8, 20-25, and 11-16, respectively, in East and South Xinjiang and Southeast Tibet. (3) The study areas were divided into four categories according to the spatiotemporal distribution of hazards. The “high hazard and rapidly increasing” and “low hazard and keep increasing” areas accounted for 8.71% and 41.33%, respectively. (4) The proportions of units with significantly increased average hazard (AH) at city and county levels were 57% and 68%, respectively. Jinhua, Zhengzhou, Nanchang, Wuhan, Shaoxing, Changsha, Shijiazhuang, Nanjing, Wuxi, and Changzhou accounted for the top 10 AH among the 49 first-tier, new first-tier, and second-tier cities. “Ten Furnaces” at the top of the provincial capitals were Zhengzhou, Nanchang, Wuhan, Changsha, Shijiazhuang, Nanjing, Hangzhou, Haikou, Chongqing, and Hefei. Suzhou’s AH rose the fastest. While the strategy of west development and of revitalizing northeast China progressed, and the urbanization level and population aging of developed areas were further developed, the continuously increasing heatwave hazard should be fully considered.

The Subpolar North Atlantic plays a critical role in the formation of the deep water masses which drive Atlantic Meridional Overturning Circulation (AMOC). Labrador Sea Water (LSW) is formed in the Labrador Sea and exported predominantly via the Deep Western Boundary Current (DWBC). The DWBC is an essential component of the AMOC advecting deep waters southward, flowing at depth along the continental slope of the western Atlantic. By combining sustained hydrographic observations from the Labrador Sea, Line W, Bermuda basin, and offshore of Abaco Island along 26.5°N, we investigate the signal propagation and advective timescales of LSW via the DWBC from its source region to the Tropical Atlantic through various approaches using robust neutral density classifications. Two individually-defined LSW classes are observed to advect on timescales that support a new plausible hydrographically-observed advective pathway. We find each LSW class to advect on independent timescales, and validate a hypothesized alternative-interior advection pathway branching from the DWBC by observing LSW outside of the DWBC in the Bermuda basin just prior to or on the same timescale as at 26.5°N- 10-15 years after leaving the source region. Advective timescales estimated herein indicate that this interior pathway is likely the main advective pathway; it remains uncertain whether a direct pathway plays a significant advective role. Using LSW convective signals as advective tracers along the DWBC permits the estimation of advective timescales from the subpolar to tropical latitudes, illuminating deep water advection pathways across the North Atlantic and the lower-limb of AMOC as a whole.

A document by Elsa Arellano-Torres. Click on the document to view its contents.

How runoff will change as atmospheric CO2 rises depends upon several difficult to project factors, including CO2 fertilization, lengthened growing seasons, and vegetation greening. However, geologic records of the hydrological response to past carbon cycle perturbations indicate large increases in runoff with higher CO2. We demonstrate that the fact that the Earth has remained habitable since life emerged sets a lower-bound on the sensitivity of runoff to CO2 changes. The recovery of the Earth system from perturbations is attributed to silicate weathering, which transfers CO2 to the oceans as alkalinity via runoff. Though many factors mediate weathering rates, runoff determines the total flux of silicate-derived cations and hence the removal flux of excess CO2. Using a carbon cycle model that parameterizes weathering as a function of rock reactivity, runoff, temperature, and soil CO2, we show that recovery from a perturbation is only possible if the lower-bound for the sensitivity of runoff to atmospheric CO2 is 0%/K. Using proxy data for the Paleocene-Eocene Thermal Maximum, we find that to match the marine d13C record requires a runoff sensitivity greater than 0%/K and similar to estimates of the modern runoff sensitivity derived from an ensemble of Earth system models. These results suggest that the processes that enhance global runoff are likely to prevail over processes that tend to dampen runoff. In turn, that the Earth has always recovered from perturbations suggests that, though the runoff response is spatially complex, global discharge has never declined in response to warming, despite quite varied paleogeographies.

Taking stock of global progress towards achieving the Paris Agreement requires measuring aggregate national action against modelled mitigation pathways. Because of differences in how land-based carbon removals are defined, scientific sources report higher global carbon emissions than national emissions inventories, a gap which will evolve in the future. We establish a first estimate aligning IPCC-assessed pathways with inventories using a climate model to explicitly include indirect carbon removal dynamics on land area reported as managed for by countries. After alignment, we find that key global mitigation benchmarks can appear more ambitious when considering this extra land sink, though changes vary amongst world regions and temperature outcomes. Our results highlight the need to enhance communication between scientific and policy communities to enable more robust alignment in the future.

A strong Southern Hemisphere (SH) sudden stratospheric warming (SSW) event occurred in September 2019 and significantly weakened the stratospheric polar vortex. Due to the positive zonal wind anomalies in the troposphere, the barotropic/baroclinic instability, primarily controlled by the horizontal/vertical wind shear, weakened in the upper troposphere at midlatitudes in late September and early October. As a result, planetary waves (PWs) were deflected equatorward near the tropopause rather than upward into the stratosphere, resulting in less perturbation to the stratospheric polar vortex. After October 15, the westward zonal wind anomalies propagate downward and reach the troposphere, increasing the tropospheric barotropic/baroclinic instability. This benefits the propagation of PWs into the stratosphere, leading to the early breaking of the stratospheric polar vortex. In turn, the SH mesosphere becomes anomalously cold due to the stratospheric wind filtering on the gravity waves (GWs), leading to the much earlier onset of SH polar mesospheric clouds (PMCs).

The study investigates how sea surface temperature (SST) anomalies surrounding the Maritime Continent (MC) modulate the impact of developing El Niño events on Indian Summer Monsoon (ISM) rainfall. Using a climate model we find that the ISM rainfall response to tropical Pacific SST anomalies of eastern and central Pacific El Niño events is sensitive to the details of cold SST anomalies surrounding the MC. Furthermore, the remote rainfall responses to regions of SST anomalies do not combine linearly and depend strongly on gradients in the SST anomaly patterns. The cold SST anomalies around the MC have a significantly larger impact on the ISM response to eastern Pacific events than to central Pacific events. These results show the usefulness of idealised modelling experiments, which offer insights into the complex interactions of the ISM with modes of climate variability.

Vegetation acts as a critical link between the geosphere, biosphere, and atmosphere, regulating the flux of water to the atmosphere via transpiration (E) and the input of carbon from the atmosphere to plants and soil via photosynthetic carbon assimilation (A). The rate of A is known to be seasonally dynamic, however, few studies have investigated how the ratio between E and A, known as the water use efficiency (WUE), changes with phenology. WUE directly impacts regional to global carbon and water cycles and lack of knowledge regarding the dynamics of WUE remains among the largest uncertainties in current earth system model (ESM) projections of carbon and water exchange in temperate forests. Here we attempt to reduce this knowledge gap by studying these dynamics across a range of eight deciduous tree species common to temperate forests of North America. Using gas exchange and spectroscopic measurements, we investigated seasonal patterns in leaf level physiological, biochemical, and anatomical properties, including the seasonal progress of WUE and foliar capacity for carbon assimilation, which corollate with seasonal leaf phenology. We incorporate these findings into a modeling framework that contains the same representation of A, E, and canopy scaling found in ESMs to explore the impact of parameterization, which tracks phenological status, on model forecasts. Our results indicate that both photosynthetic capacity and WUE are seasonally dynamic processes which are not synchronized. WUE increased from a minimum at leaf out toward a more conservative behavior at the mid-summer growth peak. This pattern was explained by a decreased stomatal aperture and a decrease in cuticular leakage with leaf aging. We also observed a seasonal increase in maximum carboxylation capacity, with maximum rates of A and modeled tree net primary productivity (NPP) occurring later toward the end of the summer. This change was primarily driven by an increase in foliar nitrogen content, and a shift in the ratio of Vcmax to Jmax between expanding and mature leaves. By applying our revised parameterization, which captures seasonal dynamics of gas exchange, into our model framework we aim to improve the process representation of leaf function in a temperate forest, and more faithfully represent dynamics of NPP and E in the early and late growth season.

A cloud event in the altitude range of 53-65 km was observed with lidars over Yanqing (40.5°N, 116°E) and Pingquan (41°N, 118.7°E) on 30 October 2018. Clouds with a multilayer structure first occurred within the line view of lidar at dawn (03:40-06:00LT). They were faint and tenuous, and the maximum volume backscatter coefficient (VBSC) was 1.4×10-10m-1sr-1. At twilight, clouds with multilayer structures were reobserved via lidars, but they became much thicker, with a maximum VBSC of 11.2×10-10m-1sr-1. The structure of the cloud layers varied with time, and they faded completely at approximately ~00:30 LT (+1 day). Measurements from SABER/TIMED were utilized for analysis, and it was found that before the onset of cloud event, a temperature anomaly occurred in the mesosphere over Beijing, and water vapor was also very abundant. The frost point temperature profile of water vapor was estimated, and lidar measurements showed that the atmospheric temperature was close to the frost point of water vapor in the vicinity of the stratopause when the mesosphere was undergoing a low-temperature phase. It was a rare mesospheric cloud event observed with lidars at rather low latitudes, and the clouds probably resulted from the nucleation of saturated water vapor due to the occurrence of a temperature anomaly in the mesosphere.

[This presentation is published at https://doi.org/10.1111/1440-1703.12317] Dead organic matter (DOM), which consists of leaf litter, fine woody debris (FWD; < 3 cm diameter), downed coarse woody debris (CWDlog), and standing or suspended coarse woody debris (CWDsnag), plays a crucial role in forest carbon cycling. However, the contributions of each DOM type on stand-scale carbon storage (necromass) and stand-scale CO2 efflux (Rstand) estimates are not well understood. In addition, there is little knowledge of the effect of each DOM type on the accuracy of stand-scale estimates of total necromass and Rstand. This study investigated characteristics of necromass and Rstand from DOM in a subtropical forest in Okinawa island, Japan, to quantify the effect of each DOM type on total necromass, total Rstand, and estimate error of total necromass and Rstand. The CWDsnag accounted for the highest proportion (54%) of total necromass (1499.7 g C m–2), followed by CWDlog (24%), FWD (11%), and leaf litter (11%). Leaf litter accounted for the highest proportion (37%) of total Rstand (340.6 g C m–2 yr–1), followed by CWDsnag (25%), CWDlog (20%), and FWD (17%). The CWDsnag was distributed locally with 173% of the coefficient of variation for necromass, which was approximately two times higher than those of leaf litter and FWD (72–73%). Our spatial analysis revealed, for accurate estimates of CWDsnag and CWDlog necromass, sampling areas of ≥ 28750 m2 and ≥ 2058‒42875 m2 were required, respectively, under the condition of 95% confidence level and 0.1 of accepted error. In summary, CWD considerably contributed to stand-scale carbon storage and efflux in this subtropical forest, resulting in a major source of errors in the stand-scale estimates. In forests where frequent tree death is likely to occur, necromass and Rstand of CWD are not negligible in considering the carbon cycling as in this study, and therefore need to be estimated accurately.

It is important that we prepare tomorrow’s scientists, decision makers, and communities to address the societal impacts of a changing climate. In order to respond to, manage, and adapt to those changes, citizens of all ages need accurate, up-to-date information, knowledge of the sciences, and analytical skills to make responsible decisions and long-term resiliency plans regarding these challenging topics. The Climate Literacy and Energy Awareness Network (CLEAN, http://cleanet.org) is 1) providing teaching resources for educators through the CLEAN Collection and pedagogical support for teaching climate and energy science; and 2) facilitating a professionally diverse community of climate and energy literacy stakeholders, called the CLEAN Network, to share and leverage efforts to extend the reach and effectiveness of climate and energy education. This presentation will provide an overview of the CLEAN web portal and techniques we have used to market it. We will showcase the CLEAN Collection, which is comprised of 700+ resources (curricula, activities, videos, visualizations, and demonstrations/experiments) that have been reviewed for scientific accuracy, pedagogical effectiveness, and technical quality. Recent activities of the CLEAN Network will be highlighted. We will present findings from our web analytics work, which monitors visitor use of the CLEAN web portal. Through analytics data, we will show evidence of successful CLEAN marketing efforts. The results of our recent pop-up survey, which has been completed by CLEAN visitors from six continents, will also be discussed. Survey results will provide detailed information about how our audiences use the web portal. We anticipate that our insights from the CLEAN network can aid other climate and energy education programs in effectively increasing the visibility of their vital work.

The study aims to enhance the accuracy of the European Centre for Medium-Range Weather Forecasts (ECMWF) and Global Ensemble Forecast System (GEFS) reference evapotranspiration forecast at short to medium range (1-7 days) using the post-processing methods: Analog technique (AN) and Simple Linear Regression (LR) over the Indian subcontinent. The FAO, Penman-Monteith (PM) equation, is used for the estimation of reference evapotranspiration (ET0) reforecasts from meteorological reforecasts from ECMWF and GEFS models. The post-processing technique AN and LR was applied to the ET0 reforecasts and compared against the ET0 estimated using observed and reanalysis dataset. The deterministic evaluation metrics, such as  Root Mean Square Error (RMSE) and Correlation Coefficient (R), were used for the performance assessment of raw ET0 forecast and post-processed ET0 forecasts. Results showed that short to medium range ET0 forecasts improved substantially using AN and LR post-processing methods over the Indian region. Assessment across the different climatic zones in India showed that raw and post-processed ET0 forecasts in the Tropical climate zone are more skillful than in the other climatic zones. A comparison of raw and post-processed ET0 forecasts across different seasons in India showed that model forecasts are more skillful during the winter season compared to the rest. Intercomparison of the models also show that overall the raw and post-processed ET0 forecasts from ECMWF are better than GEFS. Results emphasize the use of post-processing methods to enhance the skill of ET0 forecasts over the Indian subcontinent before their application in irrigation scheduling and water demand estimation purposes.

Here, we explore the importance of export productivity versus anoxia in the formation of sedimentary layers with enhanced total organic carbon (TOC) content. We use geochemical, sedimentological and micropaleontological records from two SW Sicily outcropping successions, Lido Rosello (LR) and Punta di Maiata (PM), over three mid-Pliocene precession-forced climate cycles (4.7 – 4.6 million years ago [Ma]). Grey marls, deposited during precession minima, show enhanced TOC in both records. We suggest that basin-wide, low-oxygenated bottom-waters, resulting from freshwater-induced stratification during precession minimum, was integral to preserving grey marl TOC. Furthermore, prolonged eastern Mediterranean stratification may have produced a deep chlorophyll maximum (DCM), leading to ‘shade-flora’ dominated productivity. The LR succession displays two unique laminated layers containing enhanced TOC. These laminations do not occur at specific times in the precession cycle or in time-equivalent PM samples. They are likely to have been produced by an intermittent dysoxic/anoxic pool at LR, caused by a local depression, which enhanced TOC preservation. Consequently, the laminations provide a rare window into ‘true’ eastern Mediterranean productivity conditions during precession maxima, as organic matter is typically poorly preserved during these period due to enhanced ventilation. The laminated ‘windows’ indicate that eastern Mediterranean export productivity may not have been significantly lower during precession maxima compared to precession minima, as previously thought. During these periods, productivity conditions are likely to have been comparable to the modern eastern Mediterranean, with a spring-bloom caused by enhanced winter/spring deep-water mixing preceding a summer ‘shade-flora’ bloom caused by a summer-stratification induced DCM.

The variability of the Southern Hemisphere (SH) extratropical large-scale circulation is dominated by the Southern Annular Mode (SAM), whose timescale is extensively used as a key metric in evaluating state-of-the-art climate models. Past observational and theoretical studies suggest that the SAM lacks any internally generated (intrinsic) periodicity. Here, we show, using observations and a climate model hierarchy, that the SAM has an intrinsic 150-day periodicity. This periodicity is robustly detectable in the power spectra and principal oscillation patterns (aka dynamical mode decomposition) of the zonal-mean circulation, and in hemispheric-scale precipitation and ocean surface wind stress. The 150-day period is consistent with the predictions of a new reduced-order model for the SAM, which suggests that this periodicity is tied with a complex interaction of turbulent eddies and zonal wind anomalies, as the latter propagate from low to high latitudes. These findings present a rare example of periodic oscillations arising from the internal dynamics of the extratropical turbulent circulations. Based on these findings, we further propose a new metric for evaluating climate models, and show that some of the previously reported shortcomings and improvements in simulating SAM’s variability connect to the models’ ability in reproducing this periodicity. We argue that this periodicity should be considered in evaluating climate models and understanding the past, current, and projected Southern Hemisphere climate variability.

Ice nucleation in mixed-phase clouds has recently been identified as a critical factor in projections of future climate. Here we explore how this process influences climate sensitivity using the Community Earth System Model 2 (CESM2). We find that ice nucleation affects simulated cloud feedbacks over most regions and levels of the troposphere, not just extratropical low clouds. Ice nucleation’s impact on climate sensitivity is found to primarily operate through this process’s role setting global-scale cloud phase. Conversely, whether ice nucleation is treated as aerosol-sensitive is of limited importance. In satellite-constrained model experiments, dissimilar ice nucleation realizations all result in a strongly positive total cloud feedback, as in the default CESM2. A microphysics update from CESM1 to CESM2 had substantially weakened ice nucleation, due partly to a model issue. Our findings suggest that this contributed to increased climate sensitivity by reducing global cloud phase bias, resulting in more realistic mixed-phase clouds.

Canada’s boreal forests and tundra ecosystems are responding to unprecedented climate change with implications for the global carbon (C) cycle and global climate. However, our ability to model the response of Canada’s terrestrial ecosystems to climate change is limited and there has been no comprehensive, process-based assessment of Canada’s terrestrial C cycle. We tailor the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) to Canada and evaluate its C cycling performance against independent reference data. We utilize skill scores to assess model performance against reference data alongside benchmark scores that quantify the level of agreement between the reference data sets to aid in interpretation. Our results demonstrate CLASSIC’s sensitivity to prescribed vegetation cover. They also show that the addition of five region-specific PFTs improves CLASSIC’s skill at simulating the Canadian C cycle. CLASSIC performs well when tailored to Canada, falls within the range of the reference data sets, and meets or exceeds the benchmark scores for most C cycling processes. New region-specific land cover products, well-informed plant functional type (PFT) parameterizations, and more detailed reference data sets will facilitate improvements to the representation of the terrestrial C cycle in regional and global land surface models (LSMs). Incorporating a parameterization for boreal disturbance processes and explicitly representing peatlands and permafrost soils will improve CLASSIC’s future performance in Canada and other boreal regions. This is an important step toward a comprehensive process-based assessment of Canada’s terrestrial C cycle and evaluating Canada’s net C balance under climate change.