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1.
A fully coupled regional ocean-atmosphere model system that consists of the regional spectral model and the regional ocean modeling system for atmosphere and ocean components, respectively, is applied to downscale the present climate (1985–1994) over California from a global simulation of the Community Climate System Model 3.0 (CCSM3). The horizontal resolution of the regional coupled modeling system is 10 km, while that of the CCSM3 is at a spectral truncation of T85 (approximately 1.4°). The effects of the coupling along the California coast in the boreal summer and winter are highlighted. Evaluation of the sea surface temperature (SST) and 2-m air temperature climatology shows that alleviation of the warm bias along the California coast in the global model output is clear in the regional coupled model run. The 10-m wind is also improved by reducing the northwesterly winds along the coast. The higher resolution coupling effect on the temperature and specific humidity is the largest near the surface, while the significant impact on the wind magnitude appears at a height of approximately 850-hPa heights. The frequency of the Catalina Eddy and its duration are increased by more than 60 % in the coupled downscaling, which is attributed to enhanced offshore sea-breeze. Our study indicates that coupling is vital to regional climate downscaling of mesoscale phenomena over coastal areas.  相似文献   
2.
This paper shows demonstrable improvement in the global seasonal climate predictability of boreal summer (at zero lead) and fall (at one season lead) seasonal mean precipitation and surface temperature from a two-tiered seasonal hindcast forced with forecasted SST relative to two other contemporary operational coupled ocean–atmosphere climate models. The results from an extensive set of seasonal hindcasts are analyzed to come to this conclusion. This improvement is attributed to: (1) The multi-model bias corrected SST used to force the atmospheric model. (2) The global atmospheric model which is run at a relatively high resolution of 50 km grid resolution compared to the two other coupled ocean–atmosphere models. (3) The physics of the atmospheric model, especially that related to the convective parameterization scheme. The results of the seasonal hindcast are analyzed for both deterministic and probabilistic skill. The probabilistic skill analysis shows that significant forecast skill can be harvested from these seasonal hindcasts relative to the deterministic skill analysis. The paper concludes that the coupled ocean–atmosphere seasonal hindcasts have reached a reasonable fidelity to exploit their SST anomaly forecasts to force such relatively higher resolution two tier prediction experiments to glean further boreal summer and fall seasonal prediction skill.  相似文献   
3.
This study examines a future climate change scenario over California in a 10-km coupled regional downscaling system of the Regional Spectral Model for the atmosphere and the Regional Ocean Modeling System for the ocean forced by the global Community Climate System Model version 3.0 (CCSM3). In summer, the coupled and uncoupled downscaled experiments capture the warming trend of surface air temperature, consistent with the driving CCSM3 forcing. However, the surface warming change along the California coast is weaker in the coupled downscaled experiment than it is in the uncoupled downscaling. Atmospheric cooling due to upwelling along the coast commonly appears in both the present and future climates, but the effect of upwelling is not fully compensated for by the projected large-scale warming in the coupled downscaling experiment. The projected change of extreme warm events is quite different between the coupled and uncoupled downscaling experiments, with the former projecting a more moderate change. The projected future change in precipitation is not significantly different between coupled and uncoupled downscaling. Both the coupled and uncoupled downscaling integrations predict increased onshore sea breeze change in summer daytime and reduced offshore land breeze change in summer nighttime along the coast from the Bay area to Point Conception. Compared to the simulation of present climate, the coupled and uncoupled downscaling experiments predict 17.5 % and 27.5 % fewer Catalina eddy hours in future climate respectively.  相似文献   
4.
The wet season of Florida is well defined and is invariably centered in the boreal summer season of June–July–August. In this observational study we objectively define the Length of the Wet Season (LOWS) for Florida and examine its variations with respect to El Niño and the Southern Oscillation (ENSO) and the Atlantic Warm Pool (AWP). Our study reveals that ENSO variability has a profound influence on the LOWS especially over south Florida and parts of panhandle Florida prior to 1976. In the post-1976 era the influence of ENSO has significantly diminished. Our results show that in this pre-1976 era, warm (cold) ENSO events in the boreal winter are followed by long (short) LOWS over the region. This variation is consistent with warm (cold) ENSO events influencing early (late) onset of the wet season in the region. There is significant relationship of the LOWS in south and northeast Florida with the variation of the AWP. Unlike the teleconnection with ENSO the relationship of the demise of the wet season with AWP is stronger in the post-1976 period compared to the pre-1976 period. Furthermore the variability of the LOWS has increased in the post-1976 period.  相似文献   
5.
State-of-the-art coupled global climate models are evaluated for their simulation of the Atlantic Warm Pool (AWP). Historical runs from 17 coupled climate models included in the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5) serve as the basis for this model evaluation study. The model simulations are directly compared to observations and reanalysis data to evaluate the climatological features and variability of the AWP within each individual model. Results reveal that a select number of models—namely the GISS-E2-R, CSIRO-Mk3.6, and MPI-ESM-LR—are successful at resolving an appropriately sized AWP with some reasonable climatological features. However, these three models exhibit an erroneously broad seasonal peak of the AWP, and its variability is significantly underestimated. Furthermore, all of the CMIP5 models exhibit a significant cold bias across the tropical Atlantic basin, which hinders their ability to accurately resolve the AWP.  相似文献   
6.
We present results from 20-year “high-resolution” regional climate model simulations of precipitation change for the sub-tropical island of Puerto Rico. The Japanese Meteorological Agency Non-Hydrostatic Model (NHM) operating at a 2-km grid resolution is nested inside the Regional Spectral Model (RSM) at 10-km grid resolution, which in turn is forced at the lateral boundaries by the Community Climate System Model (CCSM4). At this resolution, the climate change experiment allows for deep convection in model integrations, which is an important consideration for sub-tropical regions in general, and on islands with steep precipitation gradients in particular that strongly influence local ecological processes and the provision of ecosystem services. Projected precipitation change for this region of the Caribbean is simulated for the mid-twenty-first century (2041–2060) under the RCP8.5 climate-forcing scenario relative to the late twentieth century (1986–2005). The results show that by the mid-twenty-first century, there is an overall rainfall reduction over the island for all seasons compared to the recent climate but with diminished mid-summer drought (MSD) in the northwestern parts of the island. Importantly, extreme rainfall events on sub-daily and daily time scales also become slightly less frequent in the projected mid-twenty-first-century climate over most regions of the island.  相似文献   
7.
Skilful and reliable precipitation data are essential for seasonal hydrologic forecasting and generation of hydrological data. Although output from dynamic downscaling methods is used for hydrological application, the existence of systematic errors in dynamically downscaled data adversely affects the skill of hydrologic forecasting. This study evaluates the precipitation data derived by dynamically downscaling the global atmospheric reanalysis data by propagating them through three hydrological models. Hydrological models are calibrated for 28 watersheds located across the southeastern United States that is minimally affected by human intervention. Calibrated hydrological models are forced with five different types of datasets: global atmospheric reanalysis (National Centers for Environmental Prediction/Department of Energy Global Reanalysis and European Centre for Medium‐Range Weather Forecasts 40‐year Reanalysis) at their native resolution; dynamically downscaled global atmospheric reanalysis at 10‐km grid resolution; stochastically generated data from weather generator; bias‐corrected dynamically downscaled; and bias‐corrected global reanalysis. The reanalysis products are considered as surrogates for large‐scale observations. Our study indicates that over the 28 watersheds in the southeastern United States, the simulated hydrological response to the bias‐corrected dynamically downscaled data is superior to the other four meteorological datasets. In comparison with synthetically generated meteorological forcing (from weather generator), the dynamically downscaled data from global atmospheric reanalysis result in more realistic hydrological simulations. Therefore, we conclude that dynamical downscaling of global reanalysis, which offers data for sufficient number of years (in this case 22 years), although resource intensive, is relatively more useful than other sources of meteorological data with comparable period in simulating realistic hydrological response at watershed scales. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   
8.
Vasubandhu Misra  H. Li 《Climate Dynamics》2014,42(9-10):2491-2507
An extensive set of boreal summer seasonal hindcasts from a two tier system is compared with corresponding seasonal hindcasts from two other coupled ocean–atmosphere models for their seasonal prediction skill (for precipitation and surface temperature) of the Asian summer monsoon. The unique aspect of the two-tier system is that it is at relatively high resolution and the SST forcing is uniquely bias corrected from the multi-model averaged forecasted SST from the two coupled ocean–atmosphere models. Our analysis reveals: (a) The two-tier forecast system has seasonal prediction skill for precipitation that is comparable (over the Southeast Asian monsoon) or even higher (over the South Asian monsoon) than the coupled ocean–atmosphere. For seasonal anomalies of the surface temperature the results are more comparable across models, with all of them showing higher skill than that for precipitation. (b) Despite the improvement from the uncoupled AGCM all models in this study display a deterministic skill for seasonal precipitation anomalies over the Asian summer monsoon region to be weak. But there is useful probabilistic skill for tercile anomalies of precipitation and surface temperature that could be harvested from both the coupled and the uncoupled climate models. (c) Seasonal predictability of the South Asian summer monsoon (rainfall and temperature) does seem to stem from the remote ENSO forcing especially over the Indian monsoon region and the relatively weaker seasonal predictability in the Southeast Asian summer monsoon could be related to the comparatively weaker teleconnection with ENSO. The uncoupled AGCM with the bias corrected SST is able to leverage this teleconnection for improved seasonal prediction skill of the South Asian monsoon relative to the coupled models which display large systematic errors of the tropical SST’s.  相似文献   
9.
The Atlantic Warm Pool (AWP) region, which is comprised of the Gulf of Mexico, Caribbean Sea and parts of the northwestern tropical Atlantic Ocean, is one of the most poorly observed parts of the global oceans. This study compares three ocean reanalyses, namely the Global Ocean Data Assimilation System of National Centers for Environmental Prediction (NCEP), the Climate Forecast System Reanalysis (CFSR) of NCEP, and the Simple Ocean Data Assimilation (SODA) for its AWP variation. The surface temperature in these ocean reanalyses is also compared with that from the Extended Range SST version 3 and Optimally Interpolated SST version 2 SST analyses. In addition we also compare three atmospheric reanalyses: NCEP-NCAR (R1), NCEP-DOE (R2), and CFSR for the associated atmospheric variability with the AWP. The comparison shows that there are important differences in the climatology of the AWP and its interannual variations. There are considerable differences in the subsurface ocean manifestation of the AWP with SODA (CFSR) showing the least (largest) modulation of the subsurface ocean temperatures. The remote teleconnections with the tropical Indian Ocean are also different across the reanalyses. However, all three oceanic reanalyses consistently show the absence of any teleconnection with the eastern equatorial Pacific Ocean. The influence of the AWP on the tropospheric temperature anomalies last for up to a one season lead and it is found to be relatively weak in R1 reanalyses. A simplified SST anomaly equation initially derived for diagnosing El Niño Southern Oscillation variability is adapted for the AWP variations in this study. The analysis of this equation reveals that the main contribution of the SST variation in the AWP region is from the variability of the net heat flux. All three reanalyses consistently show that the role of the ocean advective terms, including that associated with upwelling in the AWP region, is comparatively much smaller. The covariance of the SST tendency in the AWP with the net heat flux is large, with significant contributions from the variations of the surface shortwave and longwave fluxes.  相似文献   
10.
This study examines the oceanic and atmospheric variability over the Intra-American Seas (IAS) from a 32-year integration of a 15-km coupled regional climate model consisting of the Regional Spectral Model (RSM) for the atmosphere and the Regional Ocean Modeling System (ROMS) for the ocean. It is forced at the lateral boundaries by National Centers for Environmental Prediction-Department of Energy (NCEP-DOE R-2) atmospheric global reanalysis and Simplified Ocean Data Assimilation global oceanic reanalysis. This coupled downscaling integration is a free run without any heat flux correction and is referred as the Regional Ocean–Atmosphere coupled downscaling of global Reanalysis over the Intra-American Seas (ROARS). The paper examines the fidelity of ROARS with respect to independent observations that are both satellite based and in situ. In order to provide a perspective on the fidelity of the ROARS simulation, we also compare it with the Climate Forecast System Reanalysis (CFSR), a modern global ocean–atmosphere reanalysis product. Our analysis reveals that ROARS exhibits reasonable climatology and interannual variability over the IAS region, with climatological SST errors less than 1 °C except along the coastlines. The anomaly correlation of the monthly SST and precipitation anomalies in ROARS are well over 0.5 over the Gulf of Mexico, Caribbean Sea, Western Atlantic and Eastern Pacific Oceans. A highlight of the ROARS simulation is its resolution of the loop current and the episodic eddy events off of it. This is rather poorly simulated in the CFSR. This is also reflected in the simulated, albeit, higher variance of the sea surface height in ROARS and the lack of any variability in the sea surface height of the CFSR over the IAS. However the anomaly correlations of the monthly heat content anomalies of ROARS are comparatively lower, especially over the Gulf of Mexico and the Caribbean Sea. This is a result of ROARS exhibiting a bias of underestimation (overestimation) of high (low) clouds. ROARS like CFSR is also able to capture the Caribbean Low Level Jet and its seasonal variability reasonably well.  相似文献   
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