scholarly journals A general framework for understanding the response of the water cycle to global warming over land and ocean

2014 ◽  
Vol 18 (5) ◽  
pp. 1575-1589 ◽  
Author(s):  
M. L. Roderick ◽  
F. Sun ◽  
W. H. Lim ◽  
G. D. Farquhar
Keyword(s):  
Climate Change ◽  
Energy Balance ◽  
Surface Energy Balance ◽  
Climate Models ◽  
Climate Model ◽  
Water Cycle ◽  
Local Scale ◽  
Long Wave ◽  
Local Grid ◽  
Impacts Of Climate Change

Abstract. Climate models project increases in globally averaged atmospheric specific humidity that are close to the Clausius–Clapeyron (CC) value of around 7% K−1 whilst projections for mean annual global precipitation (P) and evaporation (E) are somewhat muted at around 2% K−1. Such global projections are useful summaries but do not provide guidance at local (grid box) scales where impacts occur. To bridge that gap in spatial scale, previous research has shown that the "wet get wetter and dry get drier" relation, Δ(P − E) ∝ P − E, follows CC scaling when the projected changes are averaged over latitudinal zones. Much of the research on projected climate impacts has been based on an implicit assumption that this CC relation also holds at local (grid box) scales but this has not previously been examined. In this paper we find that the simple latitudinal average CC scaling relation does not hold at local (grid box) scales over either ocean or land. This means that in terms of P − E, the climate models do not project that the "wet get wetter and dry get drier" at the local scales that are relevant for agricultural, ecological and hydrologic impacts. In an attempt to develop a simple framework for local-scale analysis we found that the climate model output shows a remarkably close relation to the long-standing Budyko framework of catchment hydrology. We subsequently use the Budyko curve and find that the local-scale changes in P − E projected by climate models are dominated by changes in P while the changes in net irradiance at the surface due to greenhouse forcing are small and only play a minor role in changing the mean annual P − E in the climate model projections. To further understand the apparently small changes in net irradiance we also examine projections of key surface energy balance terms. In terms of global averages, we find that the climate model projections are dominated by changes in only three terms of the surface energy balance: (1) an increase in the incoming long-wave irradiance, and the respective responses (2) in outgoing long-wave irradiance and (3) in the evaporative flux, with the latter change being much smaller than the former two terms and mostly restricted to the oceans. The small fraction of the realised surface forcing that is partitioned into E explains why the hydrologic sensitivity (2% K−1) is so much smaller than CC scaling (7% K−1). Much public and scientific perception about changes in the water cycle has been based on the notion that temperature enhances E. That notion is partly true but has proved an unfortunate starting point because it has led to misleading conclusions about the impacts of climate change on the water cycle. A better general understanding of the potential impacts of climate change on water availability that are projected by climate models will surely be gained by starting with the notion that the greater the enhancement of E, the less the surface temperature increase (and vice versa). That latter notion is based on the conservation of energy and is an underlying basis of climate model projections.

scholarly journals A general framework for understanding the response of the water cycle to global warming over land and ocean

2013 ◽  
Vol 10 (12) ◽  
pp. 15263-15294 ◽  
Author(s):  
M. L. Roderick ◽  
F. Sun ◽  
W. H. Lim ◽  
G. D. Farquhar
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Climate Models ◽  
Climate Model ◽  
Water Cycle ◽  
Specific Humidity ◽  
Water Vapour Content ◽  
Long Wave ◽  
Small Change

Abstract. Climate models project increases in globally averaged atmospheric specific humidity at the Clausius–Clapeyron (CC) value of around 7% K−1 whilst projections for precipitation (P) and evaporation (E) are somewhat muted at around 2% K−1. Such global projections are useful summaries but do not provide guidance at local (grid box) scales where impacts occur. To bridge that gap in spatial scale, previous research has shown that the following relation, Δ(P − E) ∝ P − E, holds for zonal averages in climate model projections. In this paper we first test whether that relation holds at grid box scales over ocean and over land. We find that the zonally averaged relation does not hold at grid box scales. We further find that the zonally averaged relation does not hold over land – it is specific to zonal averages over the ocean. As an alternative we tested whether the long-standing Budyko framework of catchment hydrology could be used to synthesise climate model projections over land. We find that climate model projections of Δ(P − E) out to the year 2100 conform closely to the Budyko framework. The analysis also revealed that climate models project little change in the net irradiance at the surface. To understand that result we examined projections of the key surface energy balance terms. In terms of global averages, we find the climate model projections are dominated by changes in only three terms of the surface energy balance; an increase in the incoming longwave irradiance while the responses are (mostly) restricted to the outgoing longwave irradiance with a small change in the evaporative flux. Because the change in outgoing longwave irradiance is a function of the change in surface temperature, we show that the precipitation sensitivity (i.e. 2% K−1) is an accurate summary of the partitioning of the greenhouse-induced surface forcing. With that we demonstrate that the precipitation sensitivity (2% K−1) is less than the CC value (7% K−1) because most of the greenhouse-induced surface forcing is partitioned into outgoing longwave irradiance (instead of evaporation). In essence, the models respond to elevated [CO2] by an increase in atmospheric water vapour content that increases the incoming long-wave irradiance at the surface. The surface response is dominated by a near equal increase in outgoing long-wave irradiance with only minor changes in other terms of the surface energy balance.

scholarly journals Updated cloud physics in a regional atmospheric climate model improves the modelled surface energy balance of Antarctica

2014 ◽  
Vol 8 (1) ◽  
pp. 125-135 ◽  
Author(s):  
J. M. van Wessem ◽  
C. H. Reijmer ◽  
J. T. M. Lenaerts ◽  
W. J. van de Berg ◽  
M. R. van den Broeke ◽  
...  
Keyword(s):  
Heat Flux ◽  
Energy Balance ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Climate Model ◽  
Sensible Heat Flux ◽  
Sensible Heat ◽  
Ice Cloud ◽  
Long Wave ◽  
Regional Atmospheric Climate Model

Abstract. In this study the effects of changes in the physics package of the regional atmospheric climate model RACMO2 on the modelled surface energy balance, near-surface temperature and wind speed of Antarctica are presented. The physics package update primarily consists of an improved turbulent and radiative flux scheme and a revised cloud scheme that includes a parameterisation for ice cloud super-saturation. The ice cloud super-saturation has led to more moisture being transported onto the continent, resulting in more and optically thicker clouds and more downward long-wave radiation. Overall, the updated model better represents the surface energy balance, based on a comparison with >750 months of data from nine automatic weather stations located in East Antarctica. Especially the representation of the turbulent sensible heat flux and net long-wave radiative flux has improved with a decrease in biases of up to 40%. As a result, modelled surface temperatures have increased and the bias, when compared to 10 m snow temperatures from 64 ice-core observations, has decreased from −2.3 K to −1.3 K. The weaker surface temperature inversion consequently improves the representation of the sensible heat flux, whereas wind speed biases remain unchanged. However, significant model biases remain, partly because RACMO2 at a resolution of 27 km is unable to resolve steep topography.

scholarly journals The representation of location by regional climate models in complex terrain

2015 ◽  
Vol 12 (3) ◽  
pp. 3011-3028 ◽  
Author(s):  
D. Maraun ◽  
M. Widmann
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Climate Change Signal ◽  
Model Errors ◽  
Model Simulations ◽  
Local Grid ◽  
Climate Model Simulations

Abstract. To assess potential impacts of climate change for a specific location, one typically employs climate model simulations at the grid box corresponding to the same geographical location. But based on regional climate model simulations, we show that simulated climate might be systematically displaced compared to observations. In particular in the rain shadow of moutain ranges, a local grid box is therefore often not representative of observed climate: the simulated windward weather does not flow far enough across the mountains; local grid boxes experience the wrong airmasses and atmospheric circulation. In some cases, also the local climate change signal is deteriorated. Classical bias correction methods fail to correct these location errors. Often, however, a distant simulated time series is representative of the considered observed precipitation, such that a non-local bias correction is possible. These findings also clarify limitations of bias correcting global model errors, and of bias correction against station data.

Distributed climate change impacts and uncertainty throughout mountainous catchments

2020 ◽  
Author(s):  
Jorge Sebastián Moraga ◽  
Nadav Peleg ◽  
Simone Fatichi ◽  
Peter Molnar ◽  
Paolo Burlando
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Climate Change Signal ◽  
Similar Amount ◽  
Climate Variables ◽  
Distributed Hydrological Model ◽  
Space And Time ◽  
Mountainous Catchments ◽  
Impacts Of Climate Change

<p>A combination of high-resolution models in space and time was used to evaluate the impacts of climate change on streamflow statistics and their uncertainties throughout three mountainous catchments in Switzerland (Thur, K. Emme and Maggia). The two-dimensional AWE-GEN-2d model was used to simulate ensembles of gridded climate variables at an hourly and 2-km resolution based on ground and remote-sensing observations. The model was re-parametrized using the “factors of change” approach, calculated from regional climate models, and it was used to simulate ensembles of climate data until the end of the 21st century. These ensembles were subsequently used as inputs into the fully distributed hydrological model Topkapi-ETH, which is suitable for simulating streamflow over complex terrain, and considers all the relevant hydrological processes. Based on large ensembles of simulated hydrological variables, the changes of the hydrological components in space and time were evaluated along with their uncertainty due to the internal variability of the climate and the climate model selection. Results indicate a rather uniform increase in temperature for all catchments, characterized by high uncertainty toward the end of the century (with strongest increases of over 5°C). On the other hand, the magnitude and spatial patterns (namely, mountain vs valley) of change in precipitation differ between catchments, and the uncertainty of changes in extreme events is of larger magnitude than the climate change signal. The changes in climate are foreseen to affect the hydrological components in the catchments: evapotranspiration is projected to increase, while snowmelt contribution to the streamflow is expected to decrease by 50% at the end of the century. Model results indicate a decrease in streamflow at the outlet during the summer months and an increase in winter as early as the 2020-2049 period. Conversely, changes in extreme discharge show an uncertainty greater than the change signal for most climate models. Spatially heterogeneous changes in temperature and precipitation lead to elevation-dependent hydrological responses: e.g., streamflow annual means would decrease 20% in the upper reaches of the Thur catchment, while decreasing a similar amount in the downstream reaches. Correspondingly, hourly extremes are expected to decrease 20% in the upper reaches and increase up to 50% in the lowest part of the catchment. However, the signals of the change for extreme streamflow, compared to their uncertainty, are stronger for the upper parts of the river network. These results illustrate the benefit of using stochastic downscaling of climate variables to capture climate variability and assess uncertainty, and emphasize the importance of investigating the distributed impacts of climate change in mountainous areas, which may differ between high and low elevation reaches. </p>

scholarly journals Transferability Intercomparison: An Opportunity for New Insight on the Global Water Cycle and Energy Budget

2007 ◽  
Vol 88 (3) ◽  
pp. 375-384 ◽  
Author(s):  
E. S. Takle ◽  
J. Roads ◽  
B. Rockel ◽  
W. J. Gutowski ◽  
R. W. Arritt ◽  
...  
Keyword(s):  
Energy Budget ◽  
Climate Models ◽  
Climate Model ◽  
Water Cycle ◽  
Regional Climate ◽  
Climate Conditions ◽  
Continental Scale ◽  
Global Water Cycle ◽  
Wide Range ◽  
Global Water

A new approach, called transferability intercomparisons, is described for advancing both understanding and modeling of the global water cycle and energy budget. Under this approach, individual regional climate models perform simulations with all modeling parameters and parameterizations held constant over a specific period on several prescribed domains representing different climatic regions. The transferability framework goes beyond previous regional climate model intercomparisons to provide a global method for testing and improving model parameterizations by constraining the simulations within analyzed boundaries for several domains. Transferability intercomparisons expose the limits of our current regional modeling capacity by examining model accuracy on a wide range of climate conditions and realizations. Intercomparison of these individual model experiments provides a means for evaluating strengths and weaknesses of models outside their “home domains” (domain of development and testing). Reference sites that are conducting coordinated measurements under the continental-scale experiments under the Global Energy and Water Cycle Experiment (GEWEX) Hydrometeorology Panel provide data for evaluation of model abilities to simulate specific features of the water and energy cycles. A systematic intercomparison across models and domains more clearly exposes collective biases in the modeling process. By isolating particular regions and processes, regional model transferability intercomparisons can more effectively explore the spatial and temporal heterogeneity of predictability. A general improvement of model ability to simulate diverse climates will provide more confidence that models used for future climate scenarios might be able to simulate conditions on a particular domain that are beyond the range of previously observed climates.

scholarly journals Pan-spectral observing system simulation experiments of shortwave reflectance and long-wave radiance for climate model evaluation

2015 ◽  
Vol 8 (7) ◽  
pp. 1943-1954 ◽  
Author(s):  
D. R. Feldman ◽  
W. D. Collins ◽  
J. L. Paige
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Coupled Model ◽  
Climate System ◽  
Spectral Measurements ◽  
Intergovernmental Panel ◽  
Climate System Model ◽  
Detection And Attribution ◽  
Long Wave ◽  
Hadley Centre

Abstract. Top-of-atmosphere (TOA) spectrally resolved shortwave reflectances and long-wave radiances describe the response of the Earth's surface and atmosphere to feedback processes and human-induced forcings. In order to evaluate proposed long-duration spectral measurements, we have projected 21st Century changes from the Community Climate System Model (CCSM3.0) conducted for the Intergovernmental Panel on Climate Change (IPCC) A2 Emissions Scenario onto shortwave reflectance spectra from 300 to 2500 nm and long-wave radiance spectra from 2000 to 200 cm−1 at 8 nm and 1 cm−1 resolution, respectively. The radiative transfer calculations have been rigorously validated against published standards and produce complementary signals describing the climate system forcings and feedbacks. Additional demonstration experiments were performed with the Model for Interdisciplinary Research on Climate (MIROC5) and Hadley Centre Global Environment Model version 2 Earth System (HadGEM2-ES) models for the Representative Concentration Pathway 8.5 (RCP8.5) scenario. The calculations contain readily distinguishable signatures of low clouds, snow/ice, aerosols, temperature gradients, and water vapour distributions. The goal of this effort is to understand both how climate change alters reflected solar and emitted infrared spectra of the Earth and determine whether spectral measurements enhance our detection and attribution of climate change. This effort also presents a path forward to understand the characteristics of hyperspectral observational records needed to confront models and inline instrument simulation. Such simulation will enable a diverse set of comparisons between model results from coupled model intercomparisons and existing and proposed satellite instrument measurement systems.

scholarly journals Projecting malaria hazard from climate change in eastern Africa using large ensembles to estimate uncertainty

2016 ◽  
Vol 11 (1s) ◽  
Author(s):  
Joseph Leedale ◽  
Adrian M. Tompkins ◽  
Cyril Caminade ◽  
Anne E. Jones ◽  
Grigory Nikulin ◽  
...  
Keyword(s):  
Climate Change ◽  
Malaria Transmission ◽  
Climate Models ◽  
Climate Model ◽  
Eastern Africa ◽  
Future Climate Change ◽  
Climate Projections ◽  
Model Ensemble ◽  
East African Community ◽  
Recent Climate

The effect of climate change on the spatiotemporal dynamics of malaria transmission is studied using an unprecedented ensemble of climate projections, employing three diverse bias correction and downscaling techniques, in order to partially account for uncertainty in climate- driven malaria projections. These large climate ensembles drive two dynamical and spatially explicit epidemiological malaria models to provide future hazard projections for the focus region of eastern Africa. While the two malaria models produce very distinct transmission patterns for the recent climate, their response to future climate change is similar in terms of sign and spatial distribution, with malaria transmission moving to higher altitudes in the East African Community (EAC) region, while transmission reduces in lowland, marginal transmission zones such as South Sudan. The climate model ensemble generally projects warmer and wetter conditions over EAC. The simulated malaria response appears to be driven by temperature rather than precipitation effects. This reduces the uncertainty due to the climate models, as precipitation trends in tropical regions are very diverse, projecting both drier and wetter conditions with the current state-of-the-art climate model ensemble. The magnitude of the projected changes differed considerably between the two dynamical malaria models, with one much more sensitive to climate change, highlighting that uncertainty in the malaria projections is also associated with the disease modelling approach.

scholarly journals Evaluating quantile-based bias adjustment methods for climate change scenarios

2021 ◽  
Author(s):  
Fabian Lehner ◽  
Imran Nadeem ◽  
Herbert Formayer
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Meteorological Data ◽  
Climate Change Signal ◽  
Historical Period ◽  
Climate Change Scenarios ◽  
Statistical Bias ◽  
Bias Adjustment ◽  
Direct Model

Abstract. Daily meteorological data such as temperature or precipitation from climate models is needed for many climate impact studies, e.g. in hydrology or agriculture but direct model output can contain large systematic errors. Thus, statistical bias adjustment is applied to correct climate model outputs. Here we review existing statistical bias adjustment methods and their shortcomings, and present a method which we call EQA (Empirical Quantile Adjustment), a development of the methods EDCDFm and PresRAT. We then test it in comparison to two existing methods using real and artificially created daily temperature and precipitation data for Austria. We compare the performance of the three methods in terms of the following demands: (1): The model data should match the climatological means of the observational data in the historical period. (2): The long-term climatological trends of means (climate change signal), either defined as difference or as ratio, should not be altered during bias adjustment, and (3): Even models with too few wet days (precipitation above 0.1 mm) should be corrected accurately, so that the wet day frequency is conserved. EQA fulfills (1) almost exactly and (2) at least for temperature. For precipitation, an additional correction included in EQA assures that the climate change signal is conserved, and for (3), we apply another additional algorithm to add precipitation days.

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