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In the past decade, dynamical downscaling using “pseudo‐global‐warming” (PGW) techniques has been applied frequently to project regional climate change. Such techniques generate signals by adding mean global climate model (GCM)‐simulated climate change signals in temperature, moisture, and circulation to lateral and surface boundary conditions derived from reanalysis. An alternative to PGW is to downscale GCM data directly. This technique should be advantageous, especially for simulation of extremes, since it incorporates the GCM's full spectrum of changing synoptic‐scale dynamics in the regional solution. Here, we test this assumption, by comparing simulations in Europe and Western North America. We find that for warming and changes in temperature extremes, PGW often produces similar results to direct downscaling in both regions. For mean and extreme precipitation changes, PGW generally also performs surprisingly well in many cases. Moisture budget analysis in the Western North America domain reveals why. Large fractions of the downscaled hydroclimate changes arise from mean changes in large‐scale thermodynamics and circulation, that is, increases in temperature, moisture, and winds, included in PGW by design. The one component PGW may have difficulty with is the contribution from changes in synoptic‐scale variability. When this component is large, PGW performance could be degraded. Global analysis of GCM data shows there are regions where it is large or dominant. Hence, our results provide a road map to identify, through GCM analyses, the circumstances when PGW would not be expected to accurately regionalize GCM climate signals. 

Abstract Several mechanisms have been proposed to explain why the isotope ratios of precipitation vary in space and time and why they correlate with other climate variables like temperature and precipitation. Here, we argue that this behavior is best understood through the lens of radiative transfer, which treats the depletion of atmospheric vapor transport by precipitation as analogous to the attenuation of light by absorption or scattering. Building on earlier work by Siler et al., we introduce a simple model that uses the equations of radiative transfer to approximate the two-dimensional pattern of the oxygen isotope composition of precipitation (δ_p) from monthly mean hydrologic variables. The model accurately simulates the spatial and seasonal variability inδ_pwithin a state-of-the-art climate model and permits a simple decomposition ofδ_pvariability into contributions from gradients in evaporation and the length scale of vapor transport. Outside the tropics,δ_pis mostly controlled by gradients in evaporation, whose dependence on temperature explains the positive correlation betweenδ_pand temperature (i.e., the temperature effect). At low latitudes,δ_pis mostly controlled by gradients in the transport length scale, whose inverse relationship with precipitation explains the negative correlation betweenδ_pand precipitation (i.e., the amount effect). This suggests that the temperature and amount effects are both mostly explained by the variability in upstream rainout, but they reflect distinct mechanisms governing rainout at different latitudes. Significance StatementThe isotopic composition of precipitation has long been used to make inferences about past climates based on its observed relationship with precipitation in the tropics and with temperature at higher latitudes. These relationships—known as the “amount effect” and “temperature effect,” respectively—have been attributed to many different mechanisms, most of which are thought to operate at either high or low latitudes but not both. Here, we present a unified framework for interpreting the isotope variability that can explain the latitude dependence of the temperature and amount effects despite making no distinction between high and low latitudes. Although our results are generally consistent with certain interpretations of the amount effect, they suggest that the temperature effect is widely misunderstood. 

Abstract The Great Salt Lake reached the lowest water volume in its entire 170+ year record in 2022. To explain this record low we develop and apply a lake mass‐balance model and perform four simulations: one where all input and output variables are fixed to their mid‐20th century average resulting in an equilibrium lake volume, and three others where one of the input variables (precipitation or streamflow) or the output variable (evaporation) follows observations while the other two are fixed to their mid‐20th century average. Results show anomalously low streamflow accounting for the largest proportion of the lake volume departure from the equilibrium state by 2022, resulting in about three times the additional water loss over 1950–2022 as increasing evaporation, which played the second largest role. Precipitation changes played a minimal role. Though streamflow had a greater effect, the lake would not have reached the record low volume without increasing evaporation. 

Abstract The response of zonal-mean precipitation minus evaporation ( P − E ) to global warming is investigated using a moist energy balance model (MEBM) with a simple Hadley cell parameterization. The MEBM accurately emulates zonal-mean P − E change simulated by a suite of global climate models (GCMs) under greenhouse gas forcing. The MEBM also accounts for most of the intermodel differences in GCM P − E change and better emulates GCM P − E change when compared to the “wet-gets-wetter, dry-gets-drier” thermodynamic mechanism. The intermodel spread in P − E change is attributed to intermodel differences in radiative feedbacks, which account for 60%–70% of the intermodel variance, with smaller contributions from radiative forcing and ocean heat uptake. Isolating the intermodel spread of feedbacks to specific regions shows that tropical feedbacks are the primary source of intermodel spread in zonal-mean P − E change. The ability of the MEBM to emulate GCM P − E change is further investigated using idealized feedback patterns. A less negative and narrowly peaked feedback pattern near the equator results in more atmospheric heating, which strengthens the Hadley cell circulation in the deep tropics through an enhanced poleward heat flux. This pattern also increases gross moist stability, which weakens the subtropical Hadley cell circulation. These two processes in unison increase P − E in the deep tropics, decrease P − E in the subtropics, and narrow the intertropical convergence zone. Additionally, a feedback pattern that produces polar-amplified warming partially reduces the poleward moisture flux by weakening the meridional temperature gradient. It is shown that changes to the Hadley cell circulation and the poleward moisture flux are crucial for understanding the pattern of GCM P − E change under warming. Significance Statement Changes to the hydrological cycle over the twenty-first century are predicted to impact ecosystems and socioeconomic activities throughout the world. While it is broadly expected that dry regions will get drier and wet regions will get wetter, the magnitude and spatial structure of these changes remains uncertain. In this study, we use an idealized climate model, which assumes how energy is transported in the atmosphere, to understand the processes setting the pattern of precipitation and evaporation under global warming. We first use the idealized climate model to explain why comprehensive climate models predict different changes to precipitation and evaporation across a range of latitudes. We show this arises primarily from climate feedbacks, which act to amplify or dampen the amount of warming. Ocean heat uptake and radiative forcing play secondary roles but can account for a significant amount of the uncertainty in regions where ocean circulation influences the rate of warming. We further show that uncertainty in tropical feedbacks (mainly from clouds) affects changes to the hydrological cycle across a range of latitudes. We then show how the pattern of climate feedbacks affects how the patterns of precipitation and evaporation respond to climate change through a set of idealized experiments. These results show how the pattern of climate feedbacks impacts tropical hydrological changes by affecting the strength of the Hadley circulation and polar hydrological changes by affecting the transport of moisture to the high latitudes. 

Abstract Global warming is expected to cause significant changes in the pattern of precipitation minus evaporation (P−E), which represents the net flux of water from the atmosphere to the surface or, equivalently, the convergence of moisture transport within the atmosphere. In most global climate model simulations, the pattern ofP−Echange resembles an amplification of the historical pattern—a tendency known as “wet gets wetter, dry gets drier.” However, models also predict significant departures from this approximation that are not well understood. Here, we introduce a new method of decomposing the pattern ofP−Echange into contributions from various dynamic and thermodynamic mechanisms and use it to investigate the response ofP−Eto global warming within the CESM1 Large Ensemble. In contrast to previous decompositions ofP−Echange, ours incorporates changes not only in the monthly means of atmospheric winds and moisture, but also in their temporal variability, allowing us to isolate the hydrologic impacts of changes in the mean circulation, transient eddies, relative humidity, and the spatial and temporal distributions of temperature. In general, we find that changes in the mean circulation primarily control theP−Eresponse in the tropics, while temperature changes dominate at higher latitudes. Although the relative importance of specific mechanisms varies by region, at the global scale departures from the wet-gets-wetter approximation over land are primarily due to changes in the temperature lapse rate, while changes in the mean circulation, relative humidity, and horizontal temperature gradients play a secondary role. 

Extreme precipitation events are expected to increase in magnitude in response to global warming, but the magnitude of the forced response may vary considerably across distances of ~ 100 km or less. To examine the spatial variability of extreme precipitation and its sensitivity to global warming with high statistical certainty, we use a large (16,980 years), initial-condition ensemble of dynamically downscaled global climate model simulations. Under approximately 2 °C of global warming above a recent baseline period, we find large variability in the change (0 to > 60%) of the magnitude of very rare events (from 10 to 1000-year return period values of annual maxima of daily precipitation) across the western United States. Western (and predominantly windward) slopes of coastal ranges, the Cascades, and the Sierra Nevada typically show smaller increases in extreme precipitation than eastern slopes and bordering valleys and plateaus, but this pattern is less evident in the continental interior. Using the generalized extreme value shape parameter to characterize the tail of the precipitation distribution (light to heavy tail), we find that heavy tails dominate across the study region, but light tails are common on the western slopes of mountain ranges. The majority of the region shows a tendency toward heavier tails under warming, though some regions, such as plateaus of eastern Oregon and Washington, and the crest of the Sierra Nevada, show a lightening of tails. Spatially, changes in long return-period precipitation amounts appear to partially result from changes in the shape of the tail of the distribution. 

Abstract High‐resolution regional climate model (RCM) simulations of global warming consistently predict larger percentage increases in precipitation in the lee of midlatitude mountain ranges than on their windward slopes, indicating a weakening of the orographic rain shadow. This redistribution of precipitation could have profound consequences for water resources and ecosystems, but its underlying mechanisms are unknown. Here we show that rain‐shadow weakening is just one manifestation of a more general decrease in the influence of orography on precipitation under global warming. We introduce a simple model of precipitation change based on this principle, and find that it agrees well with an ensemble of high‐resolution simulations performed over the western United States. We argue that diminished orographic influence can be explained by the unique vertical structure of orographically forced ascent, which tends to maximize in the lower atmosphere where condensation is thermodynamically less sensitive to warming. 

Abstract The stable isotope ratios of oxygen and hydrogen in polar ice cores are known to record environmental change, and they have been widely used as a paleothermometer. Although it is known to be a simplification, the relationship is often explained by invoking a single condensation pathway with progressive distillation to the temperature at the location of the ice core. In reality, the physical factors are complicated, and recent studies have identified robust aspects of the hydrologic cycle’s response to climate change that could influence the isotope-temperature relationship. In this study, we introduce a new zonal-mean isotope model derived from radiative transfer theory, and incorporate it into a recently developed moist energy balance climate model (MEBM), thus providing an internally consistent representation of the tight physical coupling between temperature, hydrology, and isotope ratios in the zonal-mean climate. The isotope model reproduces the observed pattern of meteoric δ 18 O in the modern climate, and allows us to evaluate the relative importance of different processes for the temporal correlation between δ 18 O and temperature at high latitudes. We find that the positive temporal correlation in polar ice cores is predominantly a result of suppressed high-latitude evaporation with cooling, rather than local temperature changes. The same mechanism also explains the difference in the strength of the isotope-temperature relationship between Greenland and Antarctica. 

{"Abstract":["This dataset contains monthly average output files from the iCAM6\n simulations used in the manuscript "Enhancing understanding of the\n hydrological cycle via pairing of process-oriented and isotope ratio\n tracers," in review at the Journal of Advances in Modeling Earth\n Systems. A file corresponding to each of the tagged and isotopic variables\n used in this manuscript is included. Files are at 0.9° latitude x 1.25°\n longitude, and are in NetCDF format. Data from two simulations are\n included: 1) a simulation where the atmospheric model was\n "nudged" to ERA5 wind and surface pressure fields, by adding an\n additional tendency (see section 3.1 of associated manuscript), and 2) a\n simulation where the atmospheric state was allowed to freely evolve, using\n only boundary conditions imposed at the surface and top of atmosphere.\n Specific information about each of the variables provided is located in\n the "usage notes" section below. Associated article abstract:\n The hydrologic cycle couples the Earth's energy and carbon budgets\n through evaporation, moisture transport, and precipitation. Despite a\n wealth of observations and models, fundamental limitations remain in our\n capacity to deduce even the most basic properties of the hydrological\n cycle, including the spatial pattern of the residence time (RT) of water\n in the atmosphere and the mean distance traveled from evaporation sources\n to precipitation sinks. Meanwhile, geochemical tracers such as stable\n water isotope ratios provide a tool to probe hydrological processes, yet\n their interpretation remains equivocal despite several decades of use. As\n a result, there is a need for new mechanistic tools that link variations\n in water isotope ratios to underlying hydrological processes. Here we\n present a new suite of \u201cprocess-oriented tags,\u201d which we use to explicitly\n trace hydrological processes within the isotopically enabled Community\n Atmosphere Model, version 6 (iCAM6). Using these tags, we test the\n hypotheses that precipitation isotope ratios respond to parcel rainout,\n variations in atmospheric RT, and preserve information regarding\n meteorological conditions during evaporation. We present results for a\n historical simulation from 1980 to 2004, forced with winds from the ERA5\n reanalysis. We find strong evidence that precipitation isotope ratios\n record information about atmospheric rainout and meteorological conditions\n during evaporation, but little evidence that precipitation isotope ratios\n vary with water vapor RT. These new tracer methods will enable more robust\n linkages between observations of isotope ratios in the modern hydrologic\n cycle or proxies of past terrestrial environments and the environmental\n processes underlying these observations.  "],"Methods":["Details about the simulation setup can be found in section 3 of the\n associated open-source manuscript, "Enhancing understanding of the\n hydrological cycle via pairing of process\u2010oriented and isotope ratio\n tracers." In brief, we conducted two simulations of the atmosphere\n from 1980-2004 using the isotope-enabled version of the Community\n Atmosphere Model 6 (iCAM6) at 0.9x1.25° horizontal resolution, and with 30\n vertical hybrid layers spanning from the surface to ~3 hPa. In the first\n simulation, wind and surface pressure fields were "nudged"\n toward the ERA5 reanalysis dataset by adding a nudging tendency,\n preventing the model from diverging from observed/reanalysis wind fields.\n In the second simulation, no additional nudging tendency was included, and\n the model was allowed to evolve 'freely' with only boundary\n conditions provided at the top (e.g., incoming solar radiation) and bottom\n (e.g., observed sea surface temperatures) of the model. In addition to the\n isotopic variables, our simulation included a suite of\n 'process-oriented tracers,' which we describe in section 2 of\n the manuscript. These variables are meant to track a property of water\n associated with evaporation, condensation, or atmospheric transport."],"Other":["Metadata are provided about each of the files below; moreover, since the\n attached files are NetCDF data - this information is also provided with\n the data files. NetCDF metadata can be accessed using standard tools\n (e.g., ncdump). Each file has 4 variables: the tagged quantity, and the\n associated coordinate variables (time, latitude, longitude). The latter\n three are identical across all files, only the tagged quantity changes.\n Twelve files are provided for the nudged simulation, and an additional\n three are provided for the free simulations: Nudged simulation files\n iCAM6_nudged_1980-2004_mon_RHevap: Mass-weighted mean evaporation source\n property: RH (%) with respect to surface temperature.\n iCAM6_nudged_1980-2004_mon_Tevap: Mass-weighted mean evaporation source\n property: surface temperature in Kelvin\n iCAM6_nudged_1980-2004_mon_Tcond: Mass-weighted mean condensation\n property: temperature (K) iCAM6_nudged_1980-2004_mon_columnQ: Total\n (vertically integrated) precipitable water (kg/m2).  Not a tagged\n quantity, but necessary to calculate depletion times in section 4.3 (e.g.,\n Fig. 11 and 12). iCAM6_nudged_1980-2004_mon_d18O: Precipitation d18O (\u2030\n VSMOW) iCAM6_nudged_1980-2004_mon_d18Oevap_0: Mass-weighted mean\n evaporation source property - d18O of the evaporative flux (e.g., the\n 'initial' isotope ratio prior to condensation), (\u2030 VSMOW)\n iCAM6_nudged_1980-2004_mon_dxs: Precipitation deuterium excess (\u2030 VSMOW) -\n note that precipitation d2H can be calculated from this file and the\n precipitation d18O as d2H = d-excess - 8*d18O.\n iCAM6_nudged_1980-2004_mon_dexevap_0: Mass-weighted mean evaporation\n source property - deuterium excess of the evaporative flux\n iCAM6_nudged_1980-2004_mon_lnf: Integrated property - ln(f) calculated\n from the constant-fractionation d18O tracer (see section 3.2).\n iCAM6_nudged_1980-2004_mon_precip: Total precipitation rate in m/s. Note\n there is an error in the metadata in this file - it is total\n precipitation, not just convective precipitation.\n iCAM6_nudged_1980-2004_mon_residencetime: Mean atmospheric water residence\n time (in days). iCAM6_nudged_1980-2004_mon_transportdistance: Mean\n atmospheric water transport distance (in km). Free simulation files\n iCAM6_free_1980-2004_mon_d18O: Precipitation d18O (\u2030 VSMOW)\n iCAM6_free_1980-2004_mon_dxs: Precipitation deuterium excess (\u2030 VSMOW) -\n note that precipitation d2H can be calculated from this file and the\n precipitation d18O as d2H = d-excess - 8*d18O.\n iCAM6_free_1980-2004_mon_precip: Total precipitation rate in m/s. Note\n there is an error in the metadata in this file - it is total\n precipitation, not just convective precipitation."]} 

Abstract. Changes in glacier length reflect the integrated response to local fluctuations in temperature and precipitation resulting from both external forcing (e.g., volcanic eruptions or anthropogenic CO2) and internal climate variability. In order to interpret the climate history reflected in the glacier moraine record, the influence of both sources of climate variability must therefore be considered. Here we study the last millennium of glacier-length variability across the globe using a simple dynamic glacier model, which we force with temperature and precipitation time series from a 13-member ensemble of simulations from a global climate model. The ensemble allows us to quantify the contributions to glacier-length variability from external forcing (given by the ensemble mean) and internal variability (given by the ensemble spread). Within this framework, we find that internal variability is the predominant source of length fluctuations for glaciers with a shorter response time (less than a few decades). However, for glaciers with longer response timescales (more than a few decades) external forcing has a greater influence than internal variability. We further find that external forcing also dominates when the response of glaciers from widely separated regions is averaged. Single-forcing simulations indicate that, for this climate model, most of the forced response over the last millennium, pre-anthropogenic warming, has been driven by global-scale temperature change associated with volcanic aerosols.