Assessment of inter-model variability and biases of the global water cycle in CMIP3 climate models (original) (raw)
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Hydrology and Earth System Sciences, 2020
Climate extremes, such as floods and droughts, might have severe economic and societal impacts. Given the high costs associated with these events, developing early-warning systems is of high priority. Evaporation, which is driven by around 50 % of solar energy absorbed at surface of the Earth, is an important indicator of the global water budget , monsoon precipitation, drought monitoring and the hydrological cycle. Here we investigate the response of global evaporation to main modes of interannual climate variability , including the Indian Ocean Dipole (IOD), the North Atlantic Oscillation (NAO) and the El Niño-Southern Oscillation (ENSO). These climate modes may have an influence on temperature, precipitation, soil moisture and wind speed and are likely to have impacts on global evaporation. We utilized data of historical simulations and RCP8.5 (repre-sentative concentration pathway) future simulations derived from the Coupled Model Intercomparison Project Phase 5 (CMIP5). Our results indicate that ENSO is an important driver of evaporation for many regions, especially the tropical Pacific. The significant IOD influence on evaporation is limited in western tropical Indian Ocean, while NAO is more likely to have impacts on evaporation of the North Atlantic European areas. There is high agreement between models in simulating the effects of climate modes on evaporation of these regions. Land evaporation is found to be less sensitive to considered climate modes compared to oceanic evaporation. The spatial influence of major climate modes on global evaporation is slightly more significant for NAO and the IOD and slightly less significant for ENSO in the 1906-2000 period compared to the 2006-2100 period. This study allows us to obtain insight about the predictability of evaporation and hence, may improve the early-warning systems of climate extremes and water resource management.
Response of global evaporation to major climate modes in historical and future CMIP5 simulations
Hydrology and Earth System Sciences Discussions, 2019
Climate extremes, such as floods and droughts might have severe economic and societal impacts. Given the high costs associated with these events, developing early warning systems are of high priority. Evaporation, which is driven by around 50% of solar energy absorbed at surface of the Earth, is an important indicator of global water budget, monsoon precipitation, drought monitoring and hydrological cycle. Here we investigate the response of global evaporation to main 10 modes of interannual climate variability, including the Indian Ocean Dipole (IOD), the North Atlantic Oscillation (NAO) and the El Niño-Southern Oscillation (ENSO). These climate modes may have influence on temperature, precipitation, soil moisture, wind speed, and are likely to have impacts on global evaporation. We utilized data of historical simulations and RCP8.5 future simulations derived from Coupled Model Intercomparison Project Phase 5 (CMIP5). Our results indicate that ENSO is an important driver of evaporation for many regions, especially the tropical Pacific. The significant IOD influence 15 on evaporation is limited in western tropical Indian Ocean while NAO is more likely to have impacts on evaporation of the North Atlantic European areas. Land evaporation is found to be less sensitive to considered climate modes compared to oceanic evaporation. The spatial influence of major climate modes on global evaporation is slightly more significant for NAO and the IOD while slightly less significant for ENSO in the 1906-2000 period compared to the 2006-2100 period. This study allows us to obtain insight about the predictability of evaporation, and hence, may improve the early warning systems 20 of climate extremes and water resources management.
Journal of Geophysical Research, 1996
An atmospheric model incorporating energy and moisture balance equations is developed for use in process studies of the climate system. Given the sea surface temperature and specified surface wind field, the atmospheric model calculates the surface fields of air temperature, specific humidity, as well as heat and freshwater fluxes. The inclusion of the moisture balance in the atmospheric model allows the effects of latent heat transport to be included explicitly in the model. Under fixed climatological sea surface temperature (SST) and surface wind conditions, surface air temperatures, specific humidities, and surface fluxes are comparable to direct estimates. Precipitation compares less favorably with observations. As an extension to the climatological forcing case, we conduct a simple perturbation experiment in which the [1955][1956][1957][1958][1959] pentad is compared to the 1970-1974 pentad by driving the model under the respective SST fields. The model exhibits a global air temperature decrease in the latter pentad of 0.27 øC (comparable to direct estimates) with cooling in the northern hemisphere and warming in the southern hemisphere. Such large-scale cooling in our atmospheric model is driven by equivalent local changes in the prescribed SST fields, subsequently smoothed by atmospheric diffusion of heat. The interpentadal modeled differences are shown to be quite robust through model experiments using parameters representative of several different unrealistic climatologies. The resulting interpentadal difference fields change remarkably little even when the background state has changed dramatically. This emphasizes the almost linear response of the atmospheric model to the imposed SST changes. The a, tmospheric model is also coupled to an ocean general circulation model without the need for flux adjustments. This coupled climate model faithfully represents deep water formation in the North Atlantic and Southern Ocean, with upwelling throughout the Pacific and Indian Oceans. XYater mass characteristics in the vertical compare very favorably with direct observations. where (7'•, •q•), (•,,•*) are the ocean model's and observed (or apparent) surface temperature and salinity, respectively, and (7H, 7s) are the exchange coefficients vational data, over the oceans often prohibits the use of for heat and salt. While the use of (1) may be adequate prescribed surface fluxes, while the complexity as well as computational cost often prohibits the use of fully coupled ocean-atmosphere schemes. Consequently, the most prevalent. scheme utilized by ocean modelers is a NewtonJan restoring boundary condition in which the for achieving an oceanic equilibrium state, its basic assumptions preclude its use in studying the ocean's role in climate change/climate variability. In process studies of the ocean's role in climate change, mixed boundary conditions are often employed in which the salt flux is fixed, while the restoring condition on temperature is maintained. It is widely recognized that such an approach also has serious deficiencies in its representation of the atmospheric state. While the use of a restor-15,111 15,112 FANNING AND WEAVER: AN ATMOSPHERIC ENERGY-MOISTURE BALANCE ing condition on SST allows for changes in the surface heat flux due to changes in the oceanic state, the implied changes in fluxes are generally too strong [Zhang et al., 1993; Power and Kleeraan, 1994; Tziperraan et al., 1994; Mikolajewicz and Maier-Reiraer, 1994; Rahmstorf and Willebrand, 1995]. In addition, the use of a fixed salt flux does not allow for changes in the latent heat flux from the ocean (evaporation) or changes in latent heat transport (and hence precipitation) associated with changes in the oceanic state [e.g., Huang, 1993; Hughes and Weaver, 1996].
Agricultural and Forest Meteorology, 2016
The latent heat flux (LE) between the terrestrial biosphere and atmosphere is a major driver of the global hydrological cycle. In this study, we evaluated LE simulations by 45 general circulation models (GCMs) in the Coupled Model Intercomparison Project Phase 5 (CMIP5) by a comparison with eddy covariance (EC) observations from 240 globally distributed sites from 2000 to 2009. In addition, we improved global terrestrial LE estimates for different land cover types by synthesis of seven best CMIP5 models and EC observations based on a Bayesian model averaging (BMA) method. The comparison results showed substantial differences in monthly LE among all GCMs. The model CESM1-CAM5 has the best performance with the highest predictive skill and a Taylor skill score (S) from 0.51-0.75 for different land cover types. The cross-validation results illustrate that the BMA method has improved the accuracy of the CMIP5 GCM's LE simulation with a decrease in the averaged root-mean-square error (RMSE) by more than 3W/m 2 when compared to the simple model averaging (SMA) method and individual GCMs. We found an increasing trend in the BMA-based global terrestrial LE (slope of 0.018W/m 2 yr-1 , p<0.05) during the period 1970-2005. This variation may be attributed directly to the inter-annual variations in air temperature (T a), surface incident solar radiation (R s) and precipitation (P). However, our study highlights a large difference from previous studies in a continuous increasing trend after 1998, which may be caused by the combined effects of the variations of R s , T a , and P on LE for different models on these time scales. This study provides corrected-modeling evidence for an accelerated global water cycle with climate change.
Comparison of land surface humidity between observations and CMIP5 models
Earth System Dynamics
We compare the latest observational land surface humidity dataset, HadISDH, with the latest generation of climate models extracted from the CMIP5 archive and the ERA-Interim reanalysis over the period 1973 to present. The globally averaged behaviour of HadISDH and ERA-Interim are very similar in both humidity measures and air temperature, on decadal and interannual timescales. <br><br> The global average relative humidity shows a gradual increase from 1973 to 2000, followed by a steep decline in recent years. The observed specific humidity shows a steady increase in the global average during the early period but in the later period it remains approximately constant. None of the CMIP5 models or experiments capture the observed behaviour of the relative or specific humidity over the entire study period. When using an atmosphere-only model, driven by observed sea surface temperatures and radiative forcing changes, the behaviour of regional average temperature and specific h...
Journal of the Meteorological Society of Japan, 2009
Reproducibility of land-surface air temperatures and land precipitation in the twentieth century by an atmospheric general circulation model (AGCM) MJ98 was investigated focusing on long term trends and year-to-year variability. The MJ98 model was jointly developed by the Meteorological Research Institute (MRI) and the Japan Meteorological Agency (JMA), and has a 270-km horizontal grid spacing (T42) with 30 vertical levels. Forcing the MJ98 model with observed historical sea surface temperatures (SST) and observed historical CO 2 concentrations, six-member ensemble integrations were conducted for 130 years from 1872 to 2001. Simulated land-surface air temperature and land precipitation were validated against observational data of the Climate Research Unit (CRU) from 1872 to 2001 and from 1951 to 1997, respectively. The model reproduces the observed positive trend of annual mean global average land-surface air temperature as well as decadal variability and year-to-year variability. The model simulates the observed positive trend of global average land-surface air temperature for all four seasons and the annual mean, though the magnitude is underestimated. The seasonality of the simulated trend is weak compared with that of the observation. At each grid point, the model generally reproduces positive trends of annual mean temperature over land. However, the simulated trends are underestimated especially over the middle and higher latitudes of the Northern Hemisphere, which can be partly attributed to the inability of model to simulate the increasing boreal wintertime trend of the North Atlantic Oscillation (NAO) and the Arctic Oscillation (AO) over the last few decades. The model's ability to reproduce the year-to-year variability of the annual mean temperature is relatively higher in coastal regions than in inland regions. In the case of annual mean land precipitation, the model simulates the observed negative trend for the global average, its negative trend for the Northern Hemisphere, and its positive trend for the Southern Hemisphere, although these observed trends are not statistically significant. The model fails to reproduce year-to-year variability. The model generally reproduces the distribution of trend of global annual mean land precipitation, but large discrepancies between observation and simulation are found over Asia, Australia and southern Africa.
ERA-20C: An Atmospheric Reanalysis of the Twentieth Century
Journal of Climate, 2016
The ECMWF twentieth century reanalysis (ERA-20C; 1900–2010) assimilates surface pressure and marine wind observations. The reanalysis is single-member, and the background errors are spatiotemporally varying, derived from an ensemble. The atmospheric general circulation model uses the same configuration as the control member of the ERA-20CM ensemble, forced by observationally based analyses of sea surface temperature, sea ice cover, atmospheric composition changes, and solar forcing. The resulting climate trend estimations resemble ERA-20CM for temperature and the water cycle. The ERA-20C water cycle features stable precipitation minus evaporation global averages and no spurious jumps or trends. The assimilation of observations adds realism on synoptic time scales as compared to ERA-20CM in regions that are sufficiently well observed. Comparing to nighttime ship observations, ERA-20C air temperatures are 1 K colder. Generally, the synoptic quality of the product and the agreement in ...