Timescale Dependence Research Articles

Timescale Dependence of the Precipitation Response to CO2‐Induced Warming in Millennial‐Length Climate Simulations

AbstractPrevious work has shown that estimates of climate sensitivity vary over time in response to abrupt CO2 forcing in climate model simulations. The energy fluxes that drive warming in response to increasing CO2 also influence precipitation, which prompts the question: Does the precipitation response therefore also vary over time? We investigate by examining the response of precipitation to warming forced by greenhouse gases—the hydrological sensitivity—in a set of millennial‐length climate simulations with multiple climate models, Long Run Model Intercomparison Project (LongRunMIP). We compare hydrological sensitivity calculated from three different timescales of the simulations: years 1–20, 21–150, and 151–1000. We show that the hydrological sensitivity lacks a consistent dependence on timescale, in contrast to climate sensitivity. Decomposition of the surface energy budget reveals that the relative muting of the multi‐model mean hydrological sensitivity is driven by surface downwelling shortwave flux.

A New GRACE Downscaling Approach for Deriving High‐Resolution Groundwater Storage Changes Using Ground‐Based Scaling Factors

AbstractTo compensate for the coarse resolution of groundwater storage (GWS) estimation by the Gravity Recovery and Climate Experiment (GRACE) satellites and make better use of available observed groundwater‐level (GWL) data in some aquifers, a ground‐based scaling factor (SF) method is proposed here to derive high‐resolution GRACE GWS estimates. Improvement is achieved by using the gridded SF derived from assimilating ground‐based GWL observations. The proposed SF method is tested on the North China Plain (NCP, ∼140,000 km2), where a dense network of observation wells and a consistently estimated specific yield (SY) data set are available, to demonstrate its effectiveness and practical applications. The sensitivities of SF‐estimated GWS accuracy to the specification of SY and the assimilation of GWL observation data are explored through four designed numerical experiments. Results show that this novel ground‐based method can reduce the impact of SY uncertainty on GWS estimates, particularly in regions with more pronounced regional GWS trends. The accuracy of SF‐estimated GWS is primarily determined by whether the assimilated wells can reflect the regionally averaged GWS trend. GWS accuracy is less dependent on the number of available wells assimilated. The estimated GWS trend (2004–2015) in NCP is −32.6 ± 1.3 mm/yr (−4.6 ± 0.2 km3/yr), with contrasting GWS trends found in the west Piedmont Plain (∼54,000 km2, with a loss of −66.8 mm/yr) and the coastal Eastern Plain (∼20,000 km2, and a gain of +7.2 mm/yr). Despite the limitations of regional and time scale dependence inherent in SF method, this study highlights the benefits of assimilating in situ observed GWL data instead of using model simulations in estimating SF to downscale GRACE GWS to the higher‐resolution that is desired by local water resources management.

A Physically Motivated Framework to Compare the Merger Timescales of Isolated Low- and High-mass Galaxy Pairs Across Cosmic Time

The merger timescales of isolated low-mass pairs (108 < M * < 5 × 109 M ⊙) on cosmologically motivated orbits have not yet been studied in detail, though isolated high-mass pairs (5 × 109 < M * < 1011 M ⊙) have been studied extensively. It is common to apply the same separation criteria and expected merger timescales of high-mass pairs to low-mass systems, however, it is unclear if their merger timescales are similar, or if they evolve similarly with redshift. We use the Illustris TNG100 simulation to quantify the merger timescales of isolated low-mass and high-mass major pairs as a function of cosmic time, and explore how different selection criteria impact the mass and redshift dependence of merger timescales. In particular, we present a physically motivated framework for selecting pairs via a scaled separation criterion, wherein pair separations are scaled by the virial radius of the primary’s Friends-of-Friends (FoF) group halo (r sep < 1 R vir). Applying these scaled separation criteria yields equivalent merger timescales for both mass scales at all redshifts. Alternatively, static physical separation selections applied equivalently to all galaxy pairs at all redshifts lead to a difference in merger rate of up to ∼1 Gyr between low- and high-mass pairs, particularly for r sep < 150 kpc. As a result, applying the same merger timescales to physical-separation-selected pairs will lead to a bias that systematically overpredicts low-mass galaxy merger rates.

Resistively controlled primordial magnetic turbulence decay

Context. Magnetic fields generated in the early Universe undergo turbulent decay during the radiation-dominated era. The decay is governed by a decay exponent and a decay time. It has been argued that the latter is prolonged by magnetic reconnection, which depends on the microphysical resistivity and viscosity. Turbulence, on the other hand, is not usually expected to be sensitive to microphysical dissipation, which affects only very small scales. Aims. We want to test and quantify the reconnection hypothesis in decaying hydromagnetic turbulence. Methods. We performed high-resolution numerical simulations with zero net magnetic helicity using the PENCIL CODE with up to 20483 mesh points and relate the decay time to the Alfvén time for different resistivities and viscosities. Results. The decay time is found to be longer than the Alfvén time by a factor that increases with increasing Lundquist number to the 1/4 power. The decay exponent is as expected from the conservation of the Hosking integral, but a timescale dependence on resistivity is unusual for developed turbulence and not found for hydrodynamic turbulence. In two dimensions, the Lundquist number dependence is shown to be leveling off above values of ≈25 000, independently of the value of the viscosity. Conclusions. Our numerical results suggest that resistivity effects have been overestimated in earlier work. Instead of reconnection, it may be the magnetic helicity density in smaller patches that is responsible for the resistively slow decay. The leveling off at large Lundquist number cannot currently be confirmed in three dimensions.

Reversions mask the contribution of adaptive evolution in microbiomes.

When examining bacterial genomes for evidence of past selection, the results obtained depend heavily on the mutational distance between chosen genomes. Even within a bacterial species, genomes separated by larger mutational distances exhibit stronger evidence of purifying selection as assessed by , the normalized ratio of nonsynonymous to synonymous mutations. Here, we show that the classical interpretation of this scale-dependence, weak purifying selection, leads to problematic mutation accumulation when applied to available gut microbiome data. We propose an alternative, adaptive reversion model with exactly opposite implications for dynamical intuition and applications of . Reversions that occur and sweep within-host populations are nearly guaranteed in microbiomes due to large population sizes, short generation times, and variable environments. Using analytical and simulation approaches, we show that adaptive reversion can explain the decay given only dozens of locally-fluctuating selective pressures, which is realistic in the context of Bacteroides genomes. The success of the adaptive reversion model argues for interpreting low values of obtained from long-time scales with caution, as they may emerge even when adaptive sweeps are frequent. Our work thus inverts the interpretation of an old observation in bacterial evolution, illustrates the potential of mutational reversions to shape genomic landscapes over time, and highlights the importance of studying bacterial genomic evolution on short time scales.

Operational Risk Measurement: An Optimal Timescale Selection Method Based on Information Entropy

Operational risk capital is typically allocated on an annual timescale in extant research, while ignoring that the dependence between operational risk events may differ on different timescales, such as semi-annual and quarterly. This study examines whether operational risk dependence structures differ on multiple timescales and proposes an optimal timescale selection method based on information entropy theory to obtain more reasonable operational risk measurement results. Different dependence modeling methods, including linear correlation and copula functions, are employed to analyze the dependence structures on multiple timescales. The information changes between different timescales are calculated to select the optimal timescale. The empirical analysis is based on 2,024 operational risk events from 1994 to 2017 in the Chinese Operational Loss Database (COLD), which is one of the largest external operational risk datasets for the Chinese banking industry. The results reveal significant differences in operational risk dependence at different timescales which affect the operational risk measurement results. Crucially, the quarterly timescale should be considered for more reasonable measurements. The findings provide important insights for considering a more reasonable allocation of operational risk capital under multiple timescale dependence.

The universal power spectrum of quasars in optical wavelengths

Context. The optical variability of quasars is one of the few windows through which we can explore the behaviour of accretion discs around supermassive black holes. Aims. We aim to establish the dependence of variability properties, such as characteristic timescales and the variability amplitude, on basic quasar parameters such as black hole mass and the accretion rate, controlling for the rest-frame wavelength of emission. Methods. Using large catalogues of quasars, we selected the g-band light curves for 4770 objects from the Zwicky Transient Facility archive. All the selected objects fall into a narrow redshift bin, 0.6 &lt; z &lt; 0.7, but cover a wide range of accretion rates in Eddington units (REdd) and black hole masses (M). We grouped these objects into 26 independent bins according to these parameters, calculated low-resolution g-band variability power spectra for each of these bins, and approximated the power spectra with a simple analytic model that features a break at a timescale, tb. Results. We find a clear dependence of the break timescale, tb, on REdd, on top of the known dependence of tb on the black hole mass, M. In our fits, tb ∝ M0.65 − 0.55REdd0.35−0.3, where the ranges in the exponents correspond to the best-fitting parameters of different power spectrum models. This mass dependence is slightly steeper than that found in other studies. Scaling tb to the orbital timescale of the innermost stable circular orbit (ISCO), tISCO, results approximately in tb/tISCO ∝ (REdd/M)0.35. In the standard thin disc model, (REdd/M) ∝ Tmax4, where Tmax is the maximum disc temperature, so that tb/tISCO appears to scale approximately with the maximum temperature of the disc to a small power. The observed values of tb are ∼10 longer than the orbital timescale at the light-weighted average radius of the disc region emitting in the (observer frame) g-band. The different scaling of the break frequency with M and REdd shows that the shape of the variability power spectrum cannot be solely a function of the quasar luminosity, even for a single rest-frame wavelength. Finally, the best-fitting models have slopes above the break in the range between −2.5 and −3. A slope of −2, as in the damped random walk models, fits the data significantly worse.

Impact of atmospheric O3 and NO2 on the secondary sulfates in real atmosphere

As an important component of secondary aerosols, sulfate plays a crucial role in regulating atmospheric radiative balance and influencing the secondary formation of ozone (O3). In real atmosphere, atmospheric oxidants NO2 and O3 can promote the oxidation of SO2 to form sulfate (SO42−) through multiphase chemistry that occur at different time scales. Due to the combined impact of meteorology, pollution sources, atmospheric chemistry, etc., time-scale dependence of SO2-SO42− conversion makes the impact of NO2/O3 on it more complex. In this study, based on long-term time series (2013-2020) of air pollution variables from seven stations in Hong Kong, the Multifractal Detrended Cross-Correlation Analysis (MFDCCA) method has been employed to quantify the cross-correlations between SO2 and SO42− in real atmosphere at different time scales, for examining the time-scale dependence of SO2-SO42− conversion efficiency. Furthermore, the Pearson correlation analysis has been used to study the influence of NO2/O3 on SO2-SO42− conversion, and the regional and seasonal differences have been analyzed by considering factors such as meteorology, pollution sources, and regional transport. Changes in the main components of secondary aerosols are closely linked with the co-control of regional PM2.5 and O3. Therefore, the exploration of the impact of co-existing NO2/O3 gases on the secondary formation of sulfates in real atmosphere is significant.

Equity markets volatility clustering: A multiscale analysis of intraday and overnight returns

Volatility clustering, widely observed in daily equity market returns, has not been analyzed for high-resolution intraday and overnight returns, nor has its time scale dependency been systematically explored. This paper examines the volatility clustering of intraday and overnight returns in 15 global equity markets, both developed and emerging. Findings reveal universal volatility clustering in intraday and overnight returns across various time scales, from daily to monthly and beyond. It appears that the volatility clustering of overnight returns is even more pronounced than intraday returns. However, the cross clustering between two volatility series is generally weak within each market. These observations suggest both short- and long-term investment risks, providing meaningful insights for equity market investors’ risk management.

Impacts of climate timescale on the stability of trait-environment relationships.

Predictive relationships between plant traits and environmental factors can be derived at global and regional scales, informing efforts to reorient ecological models around functional traits. However, in a changing climate, the environmental variables used as predictors in such relationships are far from stationary. This could yield errors in trait-environment model predictions if timescale is not accounted for. Here, the timescale dependence of trait-environment relationships is investigated by regressing in situ trait measurements of specific leaf area, leaf nitrogen content, and wood density on local climate characteristics summarized across several increasingly long timescales. We identify contrasting responses of leaf and wood traits to climate timescale. Leaf traits are best predicted by recent climate timescales, while wood density is a longer term memory trait. The use of sub-optimal climate timescales reduces the accuracy of the resulting trait-environment relationships. This study concludes that plant traits respond to climate conditions on the timescale of tissue lifespans rather than long-term climate normals, even at large spatial scales where multiple ecological and physiological mechanisms drive trait change. Thus, determining trait-environment relationships with temporally relevant climate variables may be critical for predicting trait change in a nonstationary climate system.

Multiple evidences for molecular level heterogeneity in a non-ionic biocatalytic deep eutectic solvent

Deep eutectic solvents (DESs) are new-generation solvents with exquisite and tuneable properties. Molecular-level heterogeneity has been identified as an intriguing feature of such solvents. Herein, we examined the spatio-temporal heterogeneity of a potential non-ionic biocatalytic DES, acetamide/urea/sorbitol (0.5Ac/0.3Ur/0.2Sor), and compared the result with corresponding binary acetamide/urea (0.6Ac/0.4Ur) DES, and another related non-ionic ternary DES (0.55Ac/0.36Ur/0.09PEG). The effect of the addition of a third component on the spatio-temporal heterogeneity of a DES was investigated. The excitation wavelength-dependent emission measurement suggests an induction of spatial heterogeneity in acetamide/urea/sorbitol compared to spatially homogenous acetamide/urea and acetamide/urea/PEG. The dynamic heterogeneity measurements in terms of solvation dynamics, dielectric relaxation, and rotational/translational diffusion indicate a length and timescale dependency. Overall, acetamide/urea/sorbitol is found to be dynamically more heterogenous than the other two related DESs.

Investigating the magnitude and temporal localization of inertial particle mixing in turbulent channel flows

Mixing of inertial point particles in a turbulent channel flow at Reτ=950 is investigated by means of direct numerical simulations. We consider inertial particles, at varying Stokes number, released from pairs of sources located at different positions inside the channel and analyze the rate at which particles come into close proximity to each other. To do so, we employ a Lagrangian framework, which is suitable for the analysis of trajectories and in general for the study of mixing and dispersion problems. By varying the release position of particles along the wall-normal direction we obtain a thorough description of mixing in an anisotropic turbulent flow. Moreover, we analyze the effects of particle inertia and show that these are not univocal but also depend on the position and alignment of the sources, owing in particular to the dependence of the flow timescales on the distance from the wall.

Spectral and Imaging Diagnostics of Spatially Extended Turbulent Electron Acceleration and Transport in Solar Flares

Solar flares are efficient particle accelerators with a large fraction of released magnetic energy (10%–50%) converted into energetic particles such as hard X-ray producing electrons. This energy transfer process is not well constrained, with competing theories regarding the acceleration mechanism(s), including MHD turbulence. We perform a detailed parameter study examining how various properties of the acceleration region, including its spatial extent and the spatial distribution of turbulence, affect the observed electron properties, such as those routinely determined from X-ray imaging and spectroscopy. Here, a time-independent Fokker–Planck equation is used to describe the acceleration and transport of flare electrons through a coronal plasma of finite temperature. Motivated by recent nonthermal line broadening observations that suggested extended regions of turbulence in coronal loops, an extended turbulent acceleration region is incorporated into the model. We produce outputs for the density-weighted electron flux, a quantity directly related to observed X-rays, modeled in energy and space from the corona to chromosphere. We find that by combining several spectral and imaging diagnostics (such as spectral index differences or ratios, energy or spatial-dependent flux ratios, and electron depths into the chromosphere) the acceleration properties, including the timescale and velocity dependence, can be constrained alongside the spatial properties. Our diagnostics provide a foundation for constraining the properties of acceleration in an individual flare from X-ray imaging spectroscopy alone, and can be applied to past, current, and future observations including those from RHESSI and Solar Orbiter.

Electrochemical sensors on board a Zeppelin NT: in-flight evaluation of low-cost trace gas measurements

Abstract. In this work, we used a Zeppelin NT equipped with six sensor setups, each composed of four different low-cost electrochemical sensors (ECSs) to measure nitrogen oxides (NO and NO2), carbon monoxide, and Ox (NO2+O3) in Germany. Additionally, a MIRO MGA laser absorption spectrometer was installed as a reference device for in-flight evaluation of the ECSs. We report not only the influence of temperature on the NO and NO2 sensor outputs but also find a shorter timescale (1 s) dependence of the sensors on the relative humidity gradient. To account for these dependencies, we developed a correction method that is independent of the reference instrument. After applying this correction to all individual sensors, we compare the sensor setups with each other and to the reference device. For the intercomparison of all six setups, we find good agreements with R2≥0.8 but different precisions for each sensor in the range from 1.45 to 6.32 ppb (parts per billion). The comparison to the reference device results in an R2 of 0.88 and a slope of 0.92 for NOx (NO+NO2). Furthermore, the average noise (1σ) of the NO and NO2 sensors reduces significantly from 6.25 and 7.1 to 1.95 and 3.32 ppb, respectively. Finally, we highlight the potential use of ECSs in airborne applications by identifying different pollution sources related to industrial and traffic emissions during multiple commercial and targeted Zeppelin flights in spring 2020. These results are a first milestone towards the quality-assured use of low-cost sensors in airborne settings without a reference device, e.g., on unmanned aerial vehicles (UAVs).

Standard Cooling of Rapidly Rotating Isolated Neutron Stars in 2D

We study the long-term thermal evolution of axisymmetric rotating neutron stars in full general relativity. To this aim, we develop NSCool 2D Rot, a major upgrade to the 1D neutron stars thermal evolution code NSCool by Page. As a first application of our new code, we address the standard cooling of isolated neutron stars with rotation frequencies up to the mass shedding limit. We investigate the effects of the equation of state (EOS) by considering different combinations of core and crust EOSs. The results indicate complex time-dependent evolution of temperature distribution throughout the whole volume of the star, and in particular, in the crust. We show that most of that complexity can be attributed to the formation of a heat blob in the crust and the latitude dependence of the heat diffusion timescale through the crust.

A comparison of ancient deltaic shoreline progradation with modern deltaic progradation rates: Unravelling the temporal structure of the shallow‐marine Blackhawk Formation, Upper Cretaceous Western Interior Seaway, USA

AbstractUnderstanding how sedimentary rocks represent time is one of the significant challenges in sedimentology. Sedimentation rates retrieved from vertical sections are strongly timescale dependent, which means that we cannot use empirical rate data derived from vertical sections in modern environments to interpret the temporal structure of ancient sedimentary deposits. We use the Lower to Middle Campanian Blackhawk Formation deposits in eastern Utah and western Colorado as a natural laboratory to test a source‐to‐sink methodology circumventing this timescale dependence by relating modern progradation rates to the deltaic shoreline progradation of ancient siliciclastic rocks. Our objective is to quantify how much time is needed to account for the observed cumulative deltaic shoreline progradation recorded by the shallow‐marine sandstone bodies of the Blackhawk Formation in terms of progradation rates derived from comparable modern deltaic systems. By making the simplifying assumption that the Blackhawk Formation rocks were deposited along a linear coastline that only grew by aggradation and progradation, it is possible to argue that the stratigraphic completeness of two‐dimensional dip‐oriented stratigraphic cross‐sections through these deposits should be high. Furthermore, we hypothesise that delta progradation estimates capture a significant portion of the biostratigraphically and radiometrically constrained duration of the succession. By comparing the recorded progradation with modern progradation rates, we estimate that we need ca. 20% (median value, with minimum and maximum estimates of 2% and 300%) of the time available from biostratigraphic and radiometric dating to account for the progradation recorded by the sedimentary deposits. This indicates that long‐term progradation rates averaged over the entire duration of the Blackhawk Formation were only a factor of five times slower than the modern progradation rates derived from observations over periods that are five to six orders of magnitude shorter. We conclude that a significant amount of time is represented by prograding deltaic shoreline deposits and that by considering the cumulative shoreline progradation, we could limit the effects of timescale dependence on the rate estimates used in our analysis.

Wavelet analysis of hydro-climatic time-series and vegetation trends of the Upper Aragón catchment (Central Spanish Pyrenees)

Water managers and researchers noted with concern a nearly generalized decline in Mediterranean rivers discharge over the last decades. Changes in climatic forces (precipitation and air temperature) and land use and land cover (LULC) changes characterized by re-vegetation and greenness are the two most possible explanations for this discharge decline. The direct impact on river discharge stemming from these changes is difficult to assess and their role is generally studied separately. Here, we use the method of wavelet transformation to interpret the time-scale dependency of catchment discharge concerning the uneven temporal climatic fluctuations and re-vegetation processes. We analyzed the temporal variation of concurrent air temperature, precipitation and river discharge time-series for the Upper Aragón catchment, located in the Central Spanish Pyrenees. A long-term database collected over 60 years (1956–2020) was used. Land cover maps corresponding to different decades were used and the results indicated that the catchment experienced a significant increase in the area covered by mixed and broadleaf forests, mostly as a consequence of land abandonment. We show how temperature slightly increased and precipitation moderately decreased. However, catchment discharge experienced a sharp decline in its magnitude and also changes in its temporal variability dynamics. The relevance of the seasonal time-scales with regard to the available discharge is reduced, which strengthens the importance of the inter-annual time-scales for the catchment discharge dynamics. Furthermore, the catchment storage-discharge cycle at inter-annual time-scales is also reduced. Such changes can mostly be attributed to the changes in plant coverage, with an increasing weight in shaping hydrological processes at catchment scale due to the greenness effect. As such, we conclude that LULC changes have played a dominant role on the river discharge dynamics. Climatic trends, on the contrary, have been small, and they have played a secondary role in the decline of river discharge. Future research can use these observations to constrain the pace of upcoming water demands based on the available water resources at Mediterranean catchment scale.

Hysteresis analysis reveals dissolved carbon concentration – discharge relationships during and between storm events

The dissolved carbon concentration, which is responsible for aquatic ecosystem productivity and water quality, is tightly coupled with hydrological processes. Excess dissolved carbon may exacerbate eutrophication and hypoxia in aquatic ecosystems and lead to deterioration of water quality. Storm events dominate the dynamics of dissolved carbon concentrations, and this nonlinear behavior exhibits significant time scale dependence. Here, we identified inter- and intra-event variability in the dissolved carbon concentration–discharge (C–Q) relationship in an agriculture-intensive catchment. The driving factors of C–Q hysteresis patterns for dissolved inorganic carbon (DIC) and organic carbon (DOC) were quantified by redundancy analysis combined with hierarchical partitioning. At the inter-event scale, DIC exhibited mainly clockwise hysteresis, indicating an exhaustible, proximal source (e.g., groundwater). However, DOC hysteresis was generally counter-clockwise, indicating distal and plentiful sources (e.g., soil water) in the agricultural catchment. Hierarchical partitioning showed that total rainfall, peak discharge and flood intensity explained 28.38% of the total variation in C–Q hysteresis for DIC and 39.87% for DOC at the inter-event scale. At the intra-event scale, time series analysis of dissolved carbon concentration and discharge indicated the interconversion of supply limitation to transport limitation, which depends on the activation of the specific DIC or DOC source zones. These findings provide significant insights into understanding the dynamics of dissolved carbon during storm periods and are important for targeted watershed management practices aimed at reducing carbon loading to surface waters.

Correlations between X-ray spectral parameters of Mkn 421 using long-term Swift–XRT data

ABSTRACT We have performed a detailed analysis of the X-ray spectra of the blazar Mkn 421 using Swift–XRT observations taken between 2005 and 2020, to quantify the correlations between spectral parameters for different models. In an earlier work, it has been shown that such spectral parameter correlations obtained from a single short flare of duration ∼5 d of Mkn 421, can be used to distinguish spectrally degenerate models and provide estimates of physical quantities. In this work, we show that the results from the long-term spectral parameter correlations are consistent with those obtained from the single flare. In particular, that the observed spectral curvature is due to maximum cut-off energy in the particle distribution is ruled out. Instead, models where the curvature is due to the energy dependence of escape or acceleration time-scale of the particles are favoured. The estimated values of the physical parameters for these models are similar to the ones obtained from the single flare analysis and are somewhat incompatible with the physical assumption of the models, suggesting that more complex physical models are required. The consistency of the results obtained from the long- and short-term evolution of the source, underlines the reliability of the technique to use spectral parameter correlations to distinguish physical models.

Climate consequences of hydrogen emissions

Abstract. Given the urgency to decarbonize global energy systems, governments and industry are moving ahead with efforts to increase deployment of hydrogen technologies, infrastructure, and applications at an unprecedented pace, including USD billions in national incentives and direct investments. While zero- and low-carbon hydrogen hold great promise to help solve some of the world's most pressing energy challenges, hydrogen is also an indirect greenhouse gas whose warming impact is both widely overlooked and underestimated. This is largely because hydrogen's atmospheric warming effects are short-lived – lasting only a couple decades – but standard methods for characterizing climate impacts of gases consider only the long-term effect from a one-time pulse of emissions. For gases whose impacts are short-lived, like hydrogen, this long-term framing masks a much stronger warming potency in the near to medium term. This is of concern because hydrogen is a small molecule known to easily leak into the atmosphere, and the total amount of emissions (e.g., leakage, venting, and purging) from existing hydrogen systems is unknown. Therefore, the effectiveness of hydrogen as a decarbonization strategy, especially over timescales of several decades, remains unclear. This paper evaluates the climate consequences of hydrogen emissions over all timescales by employing already published data to assess its potency as a climate forcer, evaluate the net warming impacts from replacing fossil fuel technologies with their clean hydrogen alternatives, and estimate temperature responses to projected levels of hydrogen demand. We use the standard global warming potential metric, given its acceptance to stakeholders, and incorporate newly published equations that more fully capture hydrogen's several indirect effects, but we consider the effects of constant rather than pulse emissions over multiple time horizons. We account for a plausible range of hydrogen emission rates and include methane emissions when hydrogen is produced via natural gas with carbon capture, usage, and storage (CCUS) (“blue” hydrogen) as opposed to renewables and water (“green” hydrogen). For the first time, we show the strong timescale dependence when evaluating the climate change mitigation potential of clean hydrogen alternatives, with the emission rate determining the scale of climate benefits or disbenefits. For example, green hydrogen applications with higher-end emission rates (10 %) may only cut climate impacts from fossil fuel technologies in half over the first 2 decades, which is far from the common perception that green hydrogen energy systems are climate neutral. However, over a 100-year period, climate impacts could be reduced by around 80 %. On the other hand, lower-end emissions (1 %) could yield limited impacts on the climate over all timescales. For blue hydrogen, associated methane emissions can make hydrogen applications worse for the climate than fossil fuel technologies for several decades if emissions are high for both gases; however, blue hydrogen yields climate benefits over a 100-year period. While more work is needed to evaluate the warming impact of hydrogen emissions for specific end-use cases and value-chain pathways, it is clear that hydrogen emissions matter for the climate and warrant further attention from scientists, industry, and governments. This is critical to informing where and how to deploy hydrogen effectively in the emerging decarbonized global economy.