Future changes in orographic precipitation will have important consequences for societies and ecosystems near mountain ranges. Here we use a simple numerical model to evaluate the response of ...orographic precipitation to surface warming under idealized conditions representative of the strongest orographic storms. We find an upward shift in the pattern of condensation with warming, caused by larger fractional changes in condensation at low temperature and amplified warming aloft. As a result, the distribution of precipitation shifts downwind, causing larger fractional changes in precipitation on the lee slope than on the windward slope. Total precipitation is found to increase by a smaller fraction than near‐surface water vapor, in contrast to expected changes in other types of extreme precipitation. Factors limiting the increase in orographic precipitation include the pattern of windward ascent, leeside evaporation, and thermodynamic constraints on the change in condensation with temperature.
Key Points
Condensation shifts upward with warming due to basic thermodynamics
Leeside precipitation is more sensitive to warming than windward precipitation
The increase in extreme precipitation may be lower in mountains than elsewhere
The fractional increase in global mean precipitation (Formula: see text) is a first-order measure of the hydrological cycle intensification under anthropogenic warming. However, Formula: see text ...varies by a factor of more than three among model projections, hindering credible assessments of the associated climate impacts. The uncertainty in Formula: see text stems from uncertainty in both hydrological sensitivity (global mean precipitation increase per unit warming) and climate sensitivity (global mean temperature increase per forcing). Here, by investigating hydrological and climate sensitivities in a unified surface-energy-balance perspective, we find that both sensitivities are significantly correlated with surface shortwave cloud feedback, which is further linked to the climatological pattern of cloud shortwave effect. The observed pattern of cloud effect thus constrains both sensitivities and consequently constrains Formula: see text. The 5%-95% uncertainty range of Formula: see text from 1979-2005 to 2080-2100 under the high-emission (moderate-emission) scenario is constrained from 6.34Formula: see text3.53% (4.19Formula: see text2.28%) in the raw ensemble-model projection to 7.03Formula: see text2.59% (4.63Formula: see text1.71%). The constraint thus suggests a higher most-likely Formula: see text and reduces the uncertainty by ~25%, providing valuable information for impact assessments.
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.
Plain Language Summary
Mountains supply about half of the fresh water used by humans globally and often regulate the seasonal cycle of stream flows by accumulating snowpack during the wet season and releasing it over the dry season. Regional simulations tend to predict large future changes in the spatial pattern of precipitation in mountainous regions, but the reasons for these changes are not well understood. Here we show that the predicted patterns of precipitation change in the western US can be explained by a simple mechanism that causes the influence of mountains to weaken with increasing temperatures. We introduce a simple model of precipitation change based on this effect, and show that its predictions closely match those of far more sophisticated regional simulations of future warming over the western US.
Key Points
Orographic influence on precipitation is reduced in simulations of global warming
Fractional precipitation change scaled by warming is reproducible with a simple model
The major El Niño of 2015/16 brought significantly less precipitation to California than previous events of comparable strength, much to the disappointment of residents suffering through the state’s ...fourth consecutive year of severe drought. Here, California’s weak precipitation in 2015/16 relative to previous major El Niño events is investigated within a 40-member ensemble of atmosphere-only simulations run with historical sea surface temperatures (SSTs) and constant radiative forcing. The simulations reveal significant differences in both California precipitation and the large-scale atmospheric circulation between 2015/16 and previous strong El Niño events, which are similar to (albeit weaker than) the differences found in observations. Principal component analysis indicates that these ensemble-mean differences were likely related to a pattern of tropical SST variability with a strong signal in the Indian Ocean and western Pacific and a weaker signal in the eastern equatorial Pacific and subtropical North Atlantic. This SST pattern was missed by the majority of forecast models, which could partly explain their erroneous predictions of above-average precipitation in California in 2015/16.
The poleward branches of the Hadley Cells and the edge of the tropics show a robust poleward shift during the satellite era, leading to concerns over the possible encroachment of the globe’s ...subtropical dry zones into currently temperate climates. The extent to which this trend is caused by anthropogenic forcing versus internal variability remains the subject of considerable debate. In this study, we use a Joint EOF method to identify two distinct modes of tropical width variability: (1) an anthropogenically-forced mode, which we identify using a 20-member simulation of the historical climate, and (2) an internal mode, which we identify using a 1000-year pre-industrial control simulation. The forced mode is found to be closely related to the top of the atmosphere radiative imbalance and exhibits a long-term trend since 1860, while the internal mode is essentially indistinguishable from the El Niño Southern Oscillation. Together these two modes explain an average of 70% of the interannual variability seen in model “edge indices” over the historical period. Since 1980, the superposition of forced and internal modes has resulted in a period of accelerated Hadley Cell expansion and decelerated global warming (i.e., the “hiatus”). A comparison of the change in these modes since 1980 indicates that by 2013 the signal has emerged above the noise of internal variability in the Southern Hemisphere, but not in the Northern Hemisphere, with the latter also exhibiting strong zonal asymmetry, particularly in the North Atlantic. Our results highlight the important interplay of internal and forced modes of tropical width change and improve our understanding of the interannual variability and long-term trend seen in observations.
The influence of climate feedbacks on regional hydrological changes under warming is poorly understood. Here, a moist energy balance model (MEBM) with a Hadley Cell parameterization is used to ...isolate the influence of climate feedbacks on changes in zonal‐mean precipitation‐minus‐evaporation (P − E) under greenhouse‐gas forcing. It is shown that cloud feedbacks act to narrow bands of tropical P − E and increase P − E in the deep tropics. The surface‐albedo feedback shifts the location of maximum tropical P − E and increases P − E in the polar regions. The intermodel spread in the P − E changes associated with feedbacks arises mainly from cloud feedbacks, with the lapse‐rate and surface‐albedo feedbacks playing important roles in the polar regions. The P − E change associated with cloud feedback locking in the MEBM is similar to that of a climate model with inactive cloud feedbacks. This work highlights the unique role that climate feedbacks play in causing deviations from the “wet‐gets‐wetter, dry‐gets‐drier” paradigm.
Plain Language Summary
Climate feedbacks, which act to amplify or dampen global warming, play an important role in shaping how the climate system responds to changes in greenhouse‐gas concentrations. Here, we use an idealized climate model, which makes a simplified assumption about how energy is transported in the atmosphere, to examine how climate feedbacks influence the patterns of precipitation and evaporation change under global warming. We find that the cloud feedback acts to narrow the band of rainfall on the equator known as the Intertropical Convergence Zone and that the surface‐albedo feedback acts to shift the location of maximum rainfall. We also find that the cloud feedback accounts for most of the uncertainty associated with feedbacks in regional hydrological change under warming. The idealized model with a locked cloud feedback also simulates a change in precipitation and evaporation that is similar to a comprehensive climate model with an inactive cloud feedback.
Key Points
A moist energy balance model (MEBM) is used to investigate the influence of climate feedbacks on regional hydrological changes under warming
Cloud feedbacks act to narrow and increase tropical P − E and are the dominant source of feedback uncertainty in regional hydrological changes
The MEBM with a locked cloud feedback largely replicates a climate model with an inactive cloud feedback
Washington State’s Cascade Mountains exhibit a strong orographic rain shadow, with much wetter western slopes than eastern slopes due to prevailing westerly flow during the winter storm season. There ...is significant interannual variability in the magnitude of this rain-shadow effect, however, which has important consequences for water resource management, especially where water is a critically limited resource east of the crest. Here the influence of the large-scale circulation on the Cascade rain shadow is investigated using observations from the Snowfall Telemetry (SNOTEL) monitoring network, supplemented by stream gauge measurements. Two orthogonal indices are introduced as a basis set for representing variability in wintertime Cascade precipitation. First, the total precipitation index is a measure of regionwide precipitation and explains the majority of the variance in wintertime precipitation everywhere. Second, the rain-shadow index is a measure of the east–west precipitation gradient. It explains up to 31% of the variance west and east of the crest. A significant correlation is found between the winter-mean rain shadow and ENSO, with weak (strong) rain shadows associated with El Niño (La Niña). The analysis is supported by streamflow data from eastern and western watersheds. A preliminary review of individual storms suggests that the strongest rain shadows are associated with warm-sector events, while the weakest rain shadows occur during warm-frontal passages. This is consistent with known changes in storm tracks associated with ENSO, and a variety of mechanisms likely contribute.
The hydrologic cycle couples the Earth's energy and carbon budgets through evaporation, moisture transport, and precipitation. Despite a wealth of observations and models, fundamental limitations ...remain in our capacity to deduce even the most basic properties of the hydrological cycle, including the spatial pattern of the residence time (RT) of water in the atmosphere and the mean distance traveled from evaporation sources to precipitation sinks. Meanwhile, geochemical tracers such as stable water isotope ratios provide a tool to probe hydrological processes, yet their interpretation remains equivocal despite several decades of use. As a result, there is a need for new mechanistic tools that link variations in water isotope ratios to underlying hydrological processes. Here we present a new suite of “process‐oriented tags,” which we use to explicitly trace hydrological processes within the isotopically enabled Community Atmosphere Model, version 6 (iCAM6). Using these tags, we test the hypotheses that precipitation isotope ratios respond to parcel rainout, variations in atmospheric RT, and preserve information regarding meteorological conditions during evaporation. We present results for a historical simulation from 1980 to 2004, forced with winds from the ERA5 reanalysis. We find strong evidence that precipitation isotope ratios record information about atmospheric rainout and meteorological conditions during evaporation, but little evidence that precipitation isotope ratios vary with water vapor RT. These new tracer methods will enable more robust linkages between observations of isotope ratios in the modern hydrologic cycle or proxies of past terrestrial environments and the environmental processes underlying these observations.
Plain Language Summary
The heavy‐to‐light isotope ratio of atmospheric water, which records a wide array of water cycle processes, is readily observable and has therefore long been thought to hold much promise to help examine changes in water cycle processes. However, as multiple processes influence water isotope ratios, it is often difficult to tie observations to hydrological processes without using an atmospheric model. In this work, we develop a comprehensive set of numerical tracers to elucidate water cycle processes in the atmosphere from source to sink. In the context of water isotope ratios, these numerical tracers provide a method to explicitly test hypotheses of how variations in water isotope ratios map to underlying hydrological processes. The new tracers we outline here permit a fuller understanding of the hydrologic cycle and allow new ways to test model parameterizations and understand the processes governing hydrologic change.
Key Points
Process‐based tracers in iCAM6 allow for expanded hypothesis testing of water cycle change and more informed use of water isotope ratios
The degree of parcel rainout is a primary control on both δ18O and d‐excess, consistent with Rayleigh theory
Water vapor residence time does not strongly influence precipitation δ18O, but evaporative conditions influence precipitation d‐excess
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