Performance evaluation and bias correction of gridded precipitation products over Arun River Basin in Nepal for hydrological applications

Theoretical and Applied Climatology - An accurate estimation of precipitation amount is crucial for various studies and planning related to water resource management, effective flood prediction and...     

Sensitivity of the hydrological cycle to the parametrization of soil hydrology in a GCM

 The sensitivity of the hydrological cycle to soil hydrology is investigated with the LMD GCM. The reference simulation includes the land-surface scheme SECHIBA, with a two-reservoir scheme for soil water storage and runoff at saturation. We studied a non-linear drainage parametrization, and a distributed surface runoff parametrization, accounting for the subgrid scale variability (SSV) of soil moisture capacity, through a distribution where the shape parameter was b. GCM results show that the drainage parametrization induces significant reductions in soil moisture and evaporation rate compared to the reference simulation. They are related to changes in moisture convergence in the tropics, and to a precipitation decrease in the extratropics. When drainage is implemented, the effect of the SSV parametrization (b=0.2) is also to reduce soil moisture and evaporation rates compared to the simulation with drainage only. These changes are much smaller than the former, but the sensitivity of the hydrological cycle to the SSV parametrization is shown to be larger in dry periods, and to be enhanced by an increase of the shape parameter b. The comparison of simulated total runoffs with observed data shows that the soil hydrological parametrizations does not reduce the GCM systematic errors in the annual water balance, but that they can improve the representation of the total runoff’s annual cycle.     

气候变暖下东北地区春玉米生产潜力变化分析

针对干旱气候变化及其对淮河流域夏玉米的可能影响,基于历史灾损构建的致灾阈值模型,应用第5次耦合模式比较计划（Coupled Model Intercomparison Project Phase 5,CMIP5）中的5个全球气候模式（GCMs）和3种典型浓度路径（RCPs）情景输出的逐日气温和降水量数据,计算不同RCPs情景下致灾阈值以上气象干旱发生频率,结合承灾体的暴露度和脆弱性,构建干旱灾害风险评估模型,开展淮河流域21世纪近期（2020—2039年）、中期（2040—2069年）和远期（2070—2099年）夏玉米抽雄—乳熟期卡脖子旱风险预估。结果表明：不同气候模式对淮河流域的气温和降水量具有较好的模拟能力,气温模拟效果更佳。未来夏玉米抽雄—乳熟期将有所提前,该生育期日数缩短;预估未来淮河流域夏玉米抽雄—乳熟期气象干旱日数年际变幅大,从其线性趋势看,RCP4.5和RCP8.5情景下气象干旱日数线性趋势不明显,而RCP6.0情景下线性增加显著。在致灾因子及承灾体的综合影响下,未来淮河流域夏玉米卡脖子旱风险年际波动大,干旱灾害风险增大,21世纪各时期,其风险远期最高、中期最低;不同情景由低向高排放情景下干旱风险依次增高。预估的干旱风险空间差异明显,总体上该流域北部风险高于南部、西部高于东部。

     

On the contribution of local feedback mechanisms to the range of climate sensitivity in two GCM ensembles

Global and local feedback analysis techniques have been applied to two ensembles of mixed layer equilibrium CO₂ doubling climate change experiments, from the CFMIP (Cloud Feedback Model Intercomparison Project) and QUMP (Quantifying Uncertainty in Model Predictions) projects. Neither of these new ensembles shows evidence of a statistically significant change in the ensemble mean or variance in global mean climate sensitivity when compared with the results from the mixed layer models quoted in the Third Assessment Report of the IPCC. Global mean feedback analysis of these two ensembles confirms the large contribution made by inter-model differences in cloud feedbacks to those in climate sensitivity in earlier studies; net cloud feedbacks are responsible for 66% of the inter-model variance in the total feedback in the CFMIP ensemble and 85% in the QUMP ensemble. The ensemble mean global feedback components are all statistically indistinguishable between the two ensembles, except for the clear-sky shortwave feedback which is stronger in the CFMIP ensemble. While ensemble variances of the shortwave cloud feedback and both clear-sky feedback terms are larger in CFMIP, there is considerable overlap in the cloud feedback ranges; QUMP spans 80% or more of the CFMIP ranges in longwave and shortwave cloud feedback. We introduce a local cloud feedback classification system which distinguishes different types of cloud feedbacks on the basis of the relative strengths of their longwave and shortwave components, and interpret these in terms of responses of different cloud types diagnosed by the International Satellite Cloud Climatology Project simulator. In the CFMIP ensemble, areas where low-top cloud changes constitute the largest cloud response are responsible for 59% of the contribution from cloud feedback to the variance in the total feedback. A similar figure is found for the QUMP ensemble. Areas of positive low cloud feedback (associated with reductions in low level cloud amount) contribute most to this figure in the CFMIP ensemble, while areas of negative cloud feedback (associated with increases in low level cloud amount and optical thickness) contribute most in QUMP. Classes associated with high-top cloud feedbacks are responsible for 33 and 20% of the cloud feedback contribution in CFMIP and QUMP, respectively, while classes where no particular cloud type stands out are responsible for 8 and 21%.     

Effects of land cover change on the tropical circulation in a GCM

Multivariate statistics are used to investigate sensitivity of the tropical atmospheric circulation to scenario-based global land cover change (LCC), with the largest changes occurring in the tropics. Three simulations performed with the fully coupled Parallel Climate Model (PCM) are compared: (1) a present day control run; (2) a simulation with present day land cover and Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES) A2 greenhouse gas (GHG) projections; and (3) a simulation with SRES A2 land cover and GHG projections. Dimensionality of PCM data is reduced by projection onto a priori specified eigenvectors, consisting of Rossby and Kelvin waves produced by a linearized, reduced gravity model of the tropical circulation. A Hotelling T ² test is performed on projection amplitudes. Effects of LCC evaluated by this method are limited to diabatic heating. A statistically significant and recurrent signal is detected for 33% of all tests performed for various combinations of parameters. Taking into account uncertainties and limitations of the present methodology, this signal can be interpreted as a Rossby wave response to prescribed LCC. The Rossby waves are shallow, large-scale motions, trapped at the equator and most pronounced in boreal summer. Differences in mass and flow fields indicate a shift of the tropical Walker circulation patterns with an anomalous subsidence over tropical South America.     

Sensitivity of the thermohaline circulation in coupled oceanic GCM — atmospheric EBM experiments

We analyze the sensitivity of the oceanic thermohaline circulation (THC) regarding perturbations in fresh water flux for a range of coupled oceanic general circulation — atmospheric energy balance models. The energy balance model (EBM) predicts surface air temperature and fresh water flux and contains the feedbacks due to meridional transports of sensible and latent heat. In the coupled system we examine a negative perturbation in run-off into the southern ocean and analyze the role of changed atmospheric heat transports and fresh water flux. With mixed boundary conditions (fixed air temperature and fixed surface fresh water fluxes) the response is characterized by a completely different oceanic heat transport than in the reference case. On the other hand, the surface heat flux remains roughly constant when the air temperature can adjust in a model where no anomalous atmospheric transports are allowed. This gives an artificially stable system with nearly unchanged oceanic heat transport. However, if meridional heat transports in the atmosphere are included, the sensitivity of the system lies between the two extreme cases. We find that changes in fresh water flux are unimportant for the THC in the coupled system.     

Processes governing the predictability of the Atlantic meridional overturning circulation in a coupled GCM

The processes that govern the predictability of decadal variations in the North Atlantic meridional overturning circulation (MOC) are investigated in a long control simulation of the ECHO-G coupled atmosphere?Cocean model. We elucidate the roles of local stochastic forcing by the atmosphere, and other potential ocean processes, and use our results to build a predictive regression model. The primary influence on MOC variability is found to come from air?Csea heat fluxes over the Eastern Labrador Sea. The maximum correlation between such anomalies and the variations in the MOC occurs at a lead time of 2?years, but we demonstrate that the MOC integrates the heat flux variations over a period of 10?years. The corresponding univariate regression model accounts for 74.5% of the interannual variability in the MOC (after the Ekman component has been removed). Dense anomalies to the south of the Greenland-Scotland ridge are also shown to precede the overturning variations by 4?C6?years, and provide a second predictor. With the inclusion of this second predictor the resulting regression model explains 82.8% of the total variance of the MOC. This final bivariate model is also tested during large rapid decadal overturning events. The sign of the rapid change is always well represented by the bivariate model, but the magnitude is usually underestimated, suggesting that other processes are also important for these large rapid decadal changes in the MOC.     

Analysis of precipitation extremes in an ensemble of transient regional climate model simulations for the Rhine basin

A non-stationary index-flood model was used to analyse the 1-day summer and 5-day winter precipitation maxima in the Rhine basin in an ensemble of 15 transient regional climate model (RCM) simulations. It is assumed that the seasonal precipitation maxima follow a generalized extreme value (GEV) distribution with time varying parameters. The index-flood assumption implies that the dispersion coefficient (the ratio of the scale and the location parameters) and the shape parameter are constant over predefined regions, while the location parameter varies within these regions. A comparison with the estimates from gridded observations shows that these GEV parameters are too large in the summer season, while there is a large overestimation of the location parameter and underestimation of the dispersion coefficient in winter. However, a large part of the biases in the summer season might be due to the low number of stations used for gridding the observations. Though there is considerable variation in the changes of the extreme value distributions among the RCM simulations, common tendencies can be identified. In summer, large quantiles increase as a consequence of an increase of the dispersion coefficient, while there is almost no change of low quantiles. In winter, low quantiles increase because of an increase of the location parameter. This effect is, however, counterbalanced by a decrease of the shape parameter in most RCM simulations, resulting in only a slight increase of large quantiles. Departures from the assumed index-flood model were observed in the Alpine region in the south of the basin. This is due to the strong spatial heterogeneity in the dispersion coefficient in a number of RCM simulations and a significant altitude dependence of the trend in the location parameter in winter in five RCM simulations.     

Frequency-intensity-distribution bias correction and trend analysis of high-resolution CMIP6 precipitation data over a tropical river basin

Theoretical and Applied Climatology - Advancements in computational power have enabled general circulation models (GCMs) to simulate climate variables at a higher resolution. However, GCM outputs...     

Study of the influence of katabatic flows on the Antarctic circulation using GCM simulations

Summary A one dimensional analytical model of katabatic wind over the Antarctica has been developed. This parametric model is derived from the bulk two-layer model of Ball including the surface friction and taking into account the Earth's rotation and the geostrophic wind in the upper layer.This model is validated using the data set (70 soundings) collected during IAGO experiment at D47 (67°24S, 138°43E, altitude 1 564m), 110 km inland from the coast of Adélie Land.The parameteric model is then introduced into a GCM which is a spectral global version of the operational numerical weather prediction model used by the French weather service. The most significant effect of the parameterization is a 50 m increase of the geopotential height over the South Pole. The surface temperature at the South Pole increases (2°C) reducing the pole-midlatitude thermal gradient. The westerly circulation at 50° S is slowed down (4m/s at 850 hPa), and the surface pressure at the South Pole increases (4hPa). These results, consistent with an increase of katabatic winds, would however be improved by a better coupling between the parameterization and the GCM boundary layer.With 8 Figures     

The effect of heating anomaly on the Asian circulation—A GCM experiment

A numerical experiment was done by using the IAP 9-Level AGCM to study the effects of radiation anomaly over East Asia on the Asian general circulation. The results show that the changes of Asian summer general circula-tion are remarkable in the Indian and China southwest monsoon, precipitation in India and the Yellow River and Huaihe River valley in China and area around the north Japan, the easterly anomaly of low-level zonal wind in the tropical Pacific and so on.     

The effect of a regional increase in ocean surface roughness on the tropospheric circulation: a GCM experiment

The sensitivity of the atmospheric circulation to an increase in ocean surface roughness in the Southern Hemisphere storm track is investigated in a paired general circulation model experiment. Such a change in sea roughness could be induced by ocean waves generated by storms. Two extended permanent-July runs are made. One with standard sea surface roughness, the other with ten times as a large surface roughness over open sea poleward of 40° S. The regional increase in ocean surface roughness significantly modifies the tropospheric circulation in the Southern Hemisphere. The strongest effect is the reduction of tropospheric winds (by 2 m/s or 10%) above the area with increased roughness. The poleward eddy momentum flux is reduced in the upper troposphere and the meridional eddy sensible heat flux is reduced in the lower troposphere. Zonal mean and eddy kinetic energy are consistently reduced.     

La Plata basin precipitation variability in spring: role of remote SST forcing as simulated by GCM experiments

An ensemble of nine experiments with the same interannually varying sea surface temperature (SST), as boundary forcing, and different initial conditions is used to investigate the role of tropical oceans in modulating precipitation variability in the region of La Plata Basin (LPB). The results from the ensemble are compared with a twentieth-century experiment performed with a coupled ocean-atmosphere model, sharing the same atmospheric component. A rotated empirical orthogonal functions analysis of South America precipitation shows that the dominant mode of variability in spring is realistically captured in both experiments. Its principal component (RPC1) correlated with global SST and atmospheric fields identifies the pattern related to El Niño Southern Oscillation and its large-scale teleconnections. Overall the pattern is well simulated in the tropical southern Pacific Ocean, mainly in the ensemble, but it is absent or too weak in other oceanic areas. The coupled model experiment shows a more realistic correlation in the subtropical South Atlantic where air-sea interactions contribute to the relationship between LPB precipitation and SST. The correspondence between model and data is much improved when the composite analysis of SST and atmospheric fields is done over the ensemble members having an RPC1 in agreement with the observations: the improvement relies on avoiding climate noise by averaging only over members that are statistically similar. Furthermore, the result suggests the presence of a high level of uncertainty due to internal atmospheric variability. The analysis of some individual years selected from the model and data RPC1 comparison reveals interesting differences among rainy springs in LPB. For example, 1982, which corresponds to a strong El Niño year, represents a clean case with a distinct wave train propagating from the central Pacific and merging with another one from the eastern tropical south Indian Ocean. The year 2003 is an example of a rainy spring in LPB not directly driven by remote SST forcing. In this case the internal variability has a dominant role, as the model is not able to reproduce the correct local precipitation pattern.     

Meteorologically consistent bias correction of climate time series for agricultural models

Conventional bias correction of simulated climate time series for impact models is done separately for climate variables and hence leads to inconsistencies between them. However, agricultural models mostly use several variables, and meteorological consistency is essential. The present work points out meteorological inconsistency due to quantile mapping and describes a new method of consistent bias correction by an optimization approach. Time series of hourly precipitation and global radiation from the regional model REMO5.7 (Run UBA C20/A1B_1) were corrected with site observations from the German Meteorological Service. The results urge to check conventionally corrected series for consistency before using them for multidimensional models. Here, quantile mapping resulted in underestimation of diffuse radiation at hours with precipitation. This deficit was minimized by the developed procedure.     

Downscaling the hydrological cycle in the Mackenzie basin with the Canadian regional climate model

Abstract

The Canadian Regional Climate Model (CRCM) has been nested within the Canadian Centre for Climate Modelling and Analysis ‘ second generation General Circulation Model (GCM), for a single month simulation over the Mackenzie River Basin and environs. The purpose of the study is to assess the ability of the higher resolution CRCM to downscale the hydrological cycle of the nesting GCM. A second 1‐month experiment, in which the CRCM was nested within analyzed fields of a global data assimilation system, was also performed to examine the sensitivity of the basin moisture budget to atmospheric lateral boundary forcing.

We have found that the CRCM can produce realistic lee cyclogenesis, preferentially in the Liard sub‐basin, along with associated circulation and precipitation patterns, as well as an improved rainshadow in the lee of the Rocky Mountains compared to the GCM. While these features do quantitatively affect the monthly average climate statistics, the basin scale moisture budgets of the models were remarkably similar, though some of this agreement is due to compensating errors in the GCM. Both models produced excessive precipitation compared to a recent climatology for the region, the cause of which is traced to lateral boundary forcing. A second experiment, identical to the first except that the CRCM was forced with analyzed fields at the lateral boundaries, produced a qualitatively different basin moisture budget, including a much more realistic precipitation field. Errors in the moisture budget of the first experiment appear to be associated with the poor representation of the Aleutian Low in the GCM, and do not appear to be strongly connected to (local) surface processes within the models. This suggests that an effective strategy for modelling the hydrological cycle of the Mackenzie Basin on the fast climate timescale ‐ a major requirement of the Mackenzie GEWEX Study ‐ will involve nesting the CRCM within analyzed (or re‐analyzed) atmospheric fields.     

Statistical bias correction for daily precipitation in regional climate models over Europe

We design, apply, and validate a methodology for correcting climate model output to produce internally consistent fields that have the same statistical intensity distribution as the observations. We refer to this as a statistical bias correction. Validation of the methodology is carried out using daily precipitation fields, defined over Europe, from the ENSEMBLES climate model dataset. The bias correction is calculated using data from 1961 to 1970, without distinguishing between seasons, and applied to seasonal data from 1991 to 2000. This choice of time periods is made to maximize the lag between calibration and validation within the ERA40 reanalysis period. Results show that the method performs unexpectedly well. Not only are the mean and other moments of the intensity distribution improved, as expected, but so are a drought and a heavy precipitation index, which depend on the autocorrelation spectra. Given that the corrections were derived without seasonal distinction and are based solely on intensity distributions, a statistical quantity oblivious of temporal correlations, it is encouraging to find that the improvements are present even when seasons and temporal statistics are considered. This encourages the application of this method to multi-decadal climate projections.     

Changes of atmospheric water vapor budget in the Pearl River basin and possible implications for hydrological cycle

In this study, we thoroughly analyzed abrupt behaviors, trends, and periodicity properties of water vapor flux and moisture budget entering and exiting the four edges of the Pearl River basin based on the NCAR/NCEP reanalysis dataset by using the continuous wavelet transform and the simple two-phase linear regression technique. Possible implications for hydrological cycle and water resource management of these changes are also discussed. The results indicate that: (1) the water vapor propagating through the four edges of the Pearl River basin is decreasing, and it is particularly true for the changes of the water vapor flux exiting from the north edge of the study river basin. The transition point from increase to decrease occurs in the early 1960s; (2) The wavelet transform spectra indicate that the monthly water vapor flux through the north edge decreases and this decrease is mainly reflected by intermittent distribution of the wavelet power spectra after early 1980s. The periodicity properties of the water vapor flux through the north edge imply that the northward propagation of water vapor flux decreases after the 1980s; (3) close relations between water vapor flux, precipitation and streamflow implies that the altered hydrological cycle in the Pearl River basin is mainly manifested by seasonal shifts of water vapor flux after early 1960s. One of the direct consequences of these changes of water vapor flux is the seasonal transition of wet and dry conditions across the Pearl River basin. Regional responses of hydrological cycle to climate variation/change could be different from one river basin to another. Hydrological responses of the Pearl River basin to the global warming are mainly demonstrated by seasonal shifts of precipitation changes: winter comes to be wetter and summer tends to be dryer. The finding of the seasonal transition of precipitation in the Pearl River basin is of great scientific and practical merits in basin scale water resource management in the Pearl River basin under the changing climate and global warming in particular.     

Estimating hydrological characteristics in the Amu Darya River basin under climate change conditions

Under consideration are results of solving the problem of the river water content estimation under conditions of uncertainties of climate change forecasts and the catchment state with a reference to the Amu Darya River basin. When constructing regional climate models, one selected a multimodel approach using the results of several global models and a statistical downscaling method that made the climate scenarios more detailed. The estimates demonstrated that in the medium- and long-term perspective, the Amu Darya River runoff is expected to decrease. As a result of the Bayesian ideology application, using the calculations got with a total probability formula, a prognostic probability curve of an annual river runoff supply of the basin rivers was derived based on different weights given to the estimates of a mean value for different climate scenarios. Prognostic characteristics of the annual runoff for the Amu Darya basin rivers are estimated in a form acceptable for hydrologic and hydroeconomic application.