scholarly journals The Sensitivity of the Hydrological Cycle to Internal Climate Variability versus Anthropogenic Climate Change

2016 ◽  
Vol 29 (10) ◽  
pp. 3661-3673 ◽  
Author(s):  
Ryan J. Kramer ◽  
Brian J. Soden
Keyword(s):  
Water Vapor ◽  
Time Scales ◽  
Climate Models ◽  
Hydrological Cycle ◽  
Internal Variability ◽  
Radiative Cooling ◽  
Surface Warming ◽  
Internal Climate Variability ◽  
Radiative Processes ◽  
Global Mean

Abstract In response to rising CO2 concentrations, climate models predict that globally averaged precipitation will increase at a much slower rate than water vapor. However, some observational studies suggest that global-mean precipitation and water vapor have increased at similar rates. While the modeling results emphasize changes at multidecadal time scales where the anthropogenic signal dominates, the shorter observational record is more heavily influenced by internal variability. Whether the physical constraints on the hydrological cycle fundamentally differ between these time scales is investigated. The results of this study show that while global-mean precipitation is constrained by radiative cooling on both time scales, the effects of CO2 dominate on multidecadal time scales, acting to suppress the increase in radiative cooling with warming. This results in a smaller precipitation change compared to interannual time scales where the effects of CO2 forcing are small. It is also shown that intermodel spread in the response of atmospheric radiative cooling (and thus global-mean precipitation) to anthropogenically forced surface warming is dominated by clear-sky radiative processes and not clouds, while clouds dominate under internal variability. The findings indicate that the sensitivity of the global hydrological cycle to surface warming differs fundamentally between internal variability and anthropogenically forced changes and this has important implications for interpreting observations of the hydrological sensitivity.

scholarly journals Mean precipitation change from a deepening troposphere

2018 ◽  
Vol 115 (45) ◽  
pp. 11465-11470 ◽  
Author(s):  
Nadir Jeevanjee ◽  
David M. Romps
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Precipitation Change ◽  
Global Climate Models ◽  
Simple Theory ◽  
Radiative Cooling ◽  
Free Troposphere ◽  
Global Mean

Global climate models robustly predict that global mean precipitation should increase at roughly 2–3%K−1, but the origin of these values is not well understood. Here we develop a simple theory to help explain these values. This theory combines the well-known radiative constraint on precipitation, which says that condensation heating from precipitation is balanced by the net radiative cooling of the free troposphere, with an invariance of radiative cooling profiles when expressed in temperature coordinates. These two constraints yield a picture in which mean precipitation is controlled primarily by the depth of the troposphere, when measured in temperature coordinates. We develop this theory in idealized simulations of radiative–convective equilibrium and also demonstrate its applicability to global climate models.

scholarly journals Increased water vapour lifetime due to global warming

2019 ◽  
Author(s):  
Øivind Hodnebrog ◽  
Gunnar Myhre ◽  
Bjørn H. Samset ◽  
Kari Alterskjær ◽  
Timothy Andrews ◽  
...  
Keyword(s):  
Global Warming ◽  
Water Vapour ◽  
Solar Irradiance ◽  
Climate Models ◽  
Hydrological Cycle ◽  
Global Climate ◽  
Global Climate Models ◽  
Climate Projections ◽  
Surface Temperature Change ◽  
Surface Warming

Abstract. The relationship between changes in integrated water vapour (IWV) and precipitation can be characterized by quantifying changes in atmospheric water vapour lifetime. Precipitation isotope ratios correlate with this lifetime, a relationship that helps understand dynamical processes and may lead to improved climate projections. We investigate how water vapour and its lifetime respond to different drivers of climate change, such as greenhouse gases and aerosols. Results from 11 global climate models have been used, based on simulations where CO2, methane, solar irradiance, black carbon (BC), and sulphate have been perturbed separately. A lifetime increase from 8 to 10 days is projected between 1986–2005 and 2081–2100, under a business-as-usual pathway. By disentangling contributions from individual climate drivers, we present a physical understanding of how global warming slows down the hydrological cycle, due to longer lifetime, but still amplifies the cycle due to stronger precipitation/evaporation fluxes. The feedback response of IWV to surface temperature change differs somewhat between drivers. Fast responses amplify these differences and lead to net changes in IWV per degree surface warming ranging from 6.4±0.9 %/K for sulphate to 9.8±2 %/K for BC. While BC is the driver with the strongest increase in IWV per degree surface warming, it is also the only driver with a reduction in precipitation per degree surface warming. Consequently, increases in BC aerosol concentrations yield the strongest slowdown of the hydrological cycle among the climate drivers studied, with a change in water vapour lifetime per degree surface warming of 1.1±0.4 days/K, compared to less than 0.5 days/K for the other climate drivers (CO2, methane, solar irradiance, sulphate).

scholarly journals Processes Controlling Tropical Tropopause Temperature and Stratospheric Water Vapor in Climate Models

2015 ◽  
Vol 28 (16) ◽  
pp. 6516-6535 ◽  
Author(s):  
Steven C. Hardiman ◽  
Ian A. Boutle ◽  
Andrew C. Bushell ◽  
Neal Butchart ◽  
Mike J. P. Cullen ◽  
...  
Keyword(s):  
Water Vapor ◽  
Climate Models ◽  
Atmospheric Composition ◽  
Stratospheric Water Vapor ◽  
Vertical Advection ◽  
Radiative Processes ◽  
Microphysical Properties ◽  
Tropical Tropopause ◽  
The Tropics ◽  
Tropopause Temperature

Abstract A warm bias in tropical tropopause temperature is found in the Met Office Unified Model (MetUM), in common with most models from phase 5 of CMIP (CMIP5). Key dynamical, microphysical, and radiative processes influencing the tropical tropopause temperature and lower-stratospheric water vapor concentrations in climate models are investigated using the MetUM. A series of sensitivity experiments are run to separate the effects of vertical advection, ice optical and microphysical properties, convection, cirrus clouds, and atmospheric composition on simulated tropopause temperature and lower-stratospheric water vapor concentrations in the tropics. The numerical accuracy of the vertical advection, determined in the MetUM by the choice of interpolation and conservation schemes used, is found to be particularly important. Microphysical and radiative processes are found to influence stratospheric water vapor both through modifying the tropical tropopause temperature and through modifying upper-tropospheric water vapor concentrations, allowing more water vapor to be advected into the stratosphere. The representation of any of the processes discussed can act to significantly reduce biases in tropical tropopause temperature and stratospheric water vapor in a physical way, thereby improving climate simulations.

Thermodynamic Scaling of the Hydrological Cycle of the Last Glacial Maximum

2012 ◽  
Vol 25 (3) ◽  
pp. 992-1006 ◽  
Author(s):  
William R. Boos
Keyword(s):  
Water Vapor ◽  
Last Glacial Maximum ◽  
Climate Models ◽  
Hydrological Cycle ◽  
High Latitudes ◽  
Last Glacial ◽  
The Tropics ◽  
The Last Glacial Maximum ◽  
Circulation Changes ◽  
The Last Glacial

Abstract In climate models subject to greenhouse gas–induced warming, vertically integrated water vapor increases at nearly the same rate as its saturation value. Previous studies showed that this increase dominates circulation changes in climate models, so that precipitation minus evaporation (P − E) decreases in the subtropics and increases in the tropics and high latitudes at a rate consistent with a Clausius–Clapeyron scaling. This study examines whether the same thermodynamic scaling describes differences in the hydrological cycle between modern times and the last glacial maximum (LGM), as simulated by a suite of coupled ocean–atmosphere models. In these models, changes in water vapor between modern and LGM climates do scale with temperature according to Clausius–Clapeyron, but this thermodynamic scaling provides a poorer description of the changes in P − E. While the scaling is qualitatively consistent with simulations in the zonal mean, predicting higher P − E in the subtropics and lower P − E in the tropics and high latitudes, it fails to account for high-amplitude zonal asymmetries. Large horizontal gradients of temperature change, which are often neglected when applying the scaling to next-century warming, are shown to be important in large parts of the extratropics. However, even with this correction the thermodynamic scaling provides a poor quantitative fit to the simulations. This suggests that circulation changes play a dominant role in regional hydrological change between modern and LGM climates. Changes in transient eddy moisture transports are shown to be particularly important, even in the deep tropics. Implications for the selection and interpretation of climate proxies are discussed.

scholarly journals Detecting sulphate aerosol geoengineering with different methods

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Y. T. Eunice Lo ◽  
Andrew J. Charlton-Perez ◽  
Fraser C. Lott ◽  
Eleanor J. Highwood
Keyword(s):  
Climate Models ◽  
Surface Air Temperature ◽  
High Sensitivity ◽  
Internal Variability ◽  
Detection Methods ◽  
Sulphate Aerosol ◽  
Near Surface ◽  
Future Scenario ◽  
External Forcings ◽  
Global Mean

Abstract Sulphate aerosol injection has been widely discussed as a possible way to engineer future climate. Monitoring it would require detecting its effects amidst internal variability and in the presence of other external forcings. We investigate how the use of different detection methods and filtering techniques affects the detectability of sulphate aerosol geoengineering in annual-mean global-mean near-surface air temperature. This is done by assuming a future scenario that injects 5 Tg yr−1 of sulphur dioxide into the stratosphere and cross-comparing simulations from 5 climate models. 64% of the studied comparisons would require 25 years or more for detection when no filter and the multi-variate method that has been extensively used for attributing climate change are used, while 66% of the same comparisons would require fewer than 10 years for detection using a trend-based filter. This highlights the high sensitivity of sulphate aerosol geoengineering detectability to the choice of filter. With the same trend-based filter but a non-stationary method, 80% of the comparisons would require fewer than 10 years for detection. This does not imply sulphate aerosol geoengineering should be deployed, but suggests that both detection methods could be used for monitoring geoengineering in global, annual mean temperature should it be needed.

The Atmospheric Energy Constraint on Global-Mean Precipitation Change

2014 ◽  
Vol 27 (2) ◽  
pp. 757-768 ◽  
Author(s):  
Angeline G. Pendergrass ◽  
Dennis L. Hartmann
Keyword(s):  
Water Vapor ◽  
Temperature Increase ◽  
Longwave Radiation ◽  
Surface Fluxes ◽  
Lapse Rate ◽  
Specific Humidity ◽  
Radiative Cooling ◽  
Rate Of Increase ◽  
Precipitation Increase ◽  
Global Mean

Abstract Models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) robustly predict that the rate of increase in global-mean precipitation with global-mean surface temperature increase is much less than the rate of increase of water vapor. The goal of this paper is to explain in detail the mechanisms by which precipitation increase is constrained by radiative cooling. Changes in clear-sky atmospheric radiative cooling resulting from changes in temperature and humidity in global warming simulations are in good agreement with the multimodel, global-mean precipitation increase projected by GCMs (~1.1 W m−2 K−1). In an atmosphere with fixed specific humidity, radiative cooling from the top of the atmosphere (TOA) increases in response to a uniform temperature increase of the surface and atmosphere, while atmospheric cooling by exchange with the surface decreases because the upward emission of longwave radiation from the surface increases more than the downward longwave radiation from the atmosphere. When a fixed relative humidity (RH) assumption is made, however, uniform warming causes a much smaller increase of cooling at the TOA, and the surface contribution reverses to an increase in net cooling rate due to increased downward emission from water vapor. Sensitivity of precipitation changes to lapse rate changes is modest when RH is fixed. Carbon dioxide reduces TOA emission with only weak effects on surface fluxes, and thus suppresses precipitation. The net atmospheric cooling response and thereby the precipitation response to CO2-induced warming at fixed RH are mostly contributed by changes in surface fluxes. The role of clouds is discussed. Intermodel spread in the rate of precipitation increase across the CMIP5 simulations is attributed to differences in the atmospheric cooling.

scholarly journals Attribution of Declining Western U.S. Snowpack to Human Effects

2008 ◽  
Vol 21 (23) ◽  
pp. 6425-6444 ◽  
Author(s):  
David W. Pierce ◽  
Tim P. Barnett ◽  
Hugo G. Hidalgo ◽  
Tapash Das ◽  
Céline Bonfils ◽  
...  
Keyword(s):  
Climate Variability ◽  
Greenhouse Gases ◽  
Climate Models ◽  
Snow Water Equivalent ◽  
Hydrological Cycle ◽  
Formal Model ◽  
Model Estimate ◽  
Economic Implications ◽  
Internal Climate Variability ◽  
Detection And Attribution

Abstract Observations show snowpack has declined across much of the western United States over the period 1950–99. This reduction has important social and economic implications, as water retained in the snowpack from winter storms forms an important part of the hydrological cycle and water supply in the region. A formal model-based detection and attribution (D–A) study of these reductions is performed. The detection variable is the ratio of 1 April snow water equivalent (SWE) to water-year-to-date precipitation (P), chosen to reduce the effect of P variability on the results. Estimates of natural internal climate variability are obtained from 1600 years of two control simulations performed with fully coupled ocean–atmosphere climate models. Estimates of the SWE/P response to anthropogenic greenhouse gases, ozone, and some aerosols are taken from multiple-member ensembles of perturbation experiments run with two models. The D–A shows the observations and anthropogenically forced models have greater SWE/P reductions than can be explained by natural internal climate variability alone. Model-estimated effects of changes in solar and volcanic forcing likewise do not explain the SWE/P reductions. The mean model estimate is that about half of the SWE/P reductions observed in the west from 1950 to 1999 are the result of climate changes forced by anthropogenic greenhouse gases, ozone, and aerosols.

scholarly journals Optimal Detection of Regional Trends Using Global Data

2010 ◽  
Vol 23 (16) ◽  
pp. 4438-4446 ◽  
Author(s):  
Stephen S. Leroy ◽  
James G. Anderson
Keyword(s):  
Climate Change ◽  
Model Uncertainty ◽  
Climate Models ◽  
Region Of Interest ◽  
Internal Variability ◽  
Spatiotemporal Patterns ◽  
Optimal Detection ◽  
Internal Climate Variability ◽  
Climate Signals ◽  
Normally Distributed

Abstract A complete accounting of model uncertainty in the optimal detection of climate signals requires normalization of the signals produced by climate models; however, there is not yet a well-defined rule for the normalization. This study seeks to discover such a rule. The authors find that, to arrive at the equations of optimal detection from a general application of Bayesian statistics to the problem of climate change, it is necessary to assume that 1) the prior probability density function (PDF) for climate change is separable into independent PDFs for sensitivity and the signals’ spatiotemporal patterns; 2) postfit residuals are due to internal variability and are normally distributed; 3) the prior PDF for sensitivity is uninformative; and 4) a continuum of climate models used to estimate model uncertainty gives a normally distributed PDF for the spatiotemporal patterns for the climate signals. This study also finds that the rule for normalization of the signals’ patterns is a simple division of model-simulated climate change in any observable quantity or set of quantities by a change in a single quantity of interest such as regionally averaged temperature or precipitation. With this normalization, optimal detection yields the most probable estimates of the underlying changes in the region of interest due to external forcings. Data outside the region of interest add information that effectively suppresses the interannual fluctuations associated with internal climate variability.

scholarly journals A Method to Deconvolve Errors in GPS RO-Derived Water Vapor Histograms

2014 ◽  
Vol 31 (12) ◽  
pp. 2606-2628 ◽  
Author(s):  
E. Robert Kursinski ◽  
Thomas Gebhardt
Keyword(s):  
Water Vapor ◽  
Climate Models ◽  
Hydrological Cycle ◽  
Direct Method ◽  
Full Range ◽  
Specific Humidity ◽  
Limited Information ◽  
Random Errors ◽  
Weather And Climate ◽  
Low Latitudes

Abstract Water vapor is an important constituent in the earth’s atmosphere that must be understood to predict weather and climate. Water vapor is challenging to measure, and observations of water vapor must be as independent of weather and climate models as possible in order to assess and improve those models. When combined with independent atmospheric temperature estimates, GPS radio occultation (RO) refractivity profiles yield unique, all-weather, high-vertical-resolution, globally distributed profiles of tropospheric water vapor whose vertical extent is maximum at low latitudes. A method for retrieving water vapor, known as the direct method, combines GPS RO-derived refractivity with temperatures from global weather analyses. Unlike variational methods, the direct method does not use the water vapor estimates from analyses because of their potential systematic errors. While utilization of the direct method has been limited because it produces negative values, these unphysical negative values reveal unique information about errors. A deconvolution technique is presented here that uses the negative values to estimate and remove random errors in histograms of water vapor derived via the direct method. Results indicate direct method specific humidity errors at low latitudes range from 0.4 g kg−1 at 725 hPa to 0.14 g kg−1 near 350 hPa, which can be removed via deconvolution. The deconvolved histograms extend to about the 240-K level in the troposphere, corresponding to 10 km at low latitudes. Unlike the limited information of low-order statistical moments like means and variances, histograms capture the full range of variability, which opens a new window into water vapor behavior and increases understanding of processes at work in the hydrological cycle.

Detection and attribution of seasonal temperature changes in India with climate models in the CMIP5 archive

2015 ◽  
Vol 7 (1) ◽  
pp. 83-102 ◽  
Author(s):  
P. Sonali ◽  
D. Nagesh Kumar
Keyword(s):  
Climate Models ◽  
Internal Variability ◽  
Causative Factor ◽  
Temporal Variations ◽  
Seasonal Temperature ◽  
Temperature Changes ◽  
Model Simulations ◽  
Internal Climate Variability ◽  
Detection And Attribution ◽  
Attribution Analysis

This study analyzes the change in annual and seasonal maximum and minimum temperature (Tmax and Tmin) during the period 1950–2005 (i.e., second half of the 20th century). In-depth analyses have been carried out for all over India as well as for five temperature homogenous regions of India separately. First, the temporal variations of annual and seasonal Tmax and Tmin are analyzed, employing the trend free pre-whitening Mann-Kendall approach. Secondly, it is assessed whether the observations contain significant signals above the natural internal variability determined from a long ‘piControl’ experiment, using Monte Carlo simulation. Thirdly, fingerprint based formal detection and attribution analysis is used to determine the signal strengths of observed and model simulations with respect to different considered experiments. Finally, these signal strengths are compared to attribute the observed changes in Tmax and Tmin to different factors. All the model simulated datasets are retrieved from the CMIP5 archive. It is noticed that the emergence of observed trends is more pronounced in Tmin compared to Tmax. Although observed changes are not solely associated with one specific causative factor, most of the changes in Tmin lie above the bounds of natural internal climate variability.

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