Shuyan Liu

Observed Diurnal Cycle Climatology of Planetary Boundary Layer Height

Abstract An observational climatology of the planetary boundary layer height (PBLH) diurnal cycle, specific to surface characteristics, is derived from 58 286 fine-resolution soundings collected in 14 major field campaigns around the world. An objective algorithm determining PBLH from sounding profiles is first developed and then verified by available lidar and sodar retrievals. The algorithm is robust and produces realistic PBLH as validated by visual examination of several thousand additional soundings. The resulting PBLH from all existing data is then subject to various statistical analyses. It is demonstrated that PBLH occurrence frequencies under stable, neutral, and unstable regimes follow a narrow, intermediate, and wide Gamma distribution, respectively, over both land and oceans. Over ice all exhibit a narrow distribution. The climatological PBLH diurnal cycle is strong over land and oceans, with a distinct peak at 1500 and 1200 LT, whereas the cycle is weak over ice. Relative to midlatitude land,...

Regional Climate–Weather Research and Forecasting Model

The CWRF is developed as a climate extension of the Weather Research and Forecasting model (WRF) by incorporating numerous improvements in the representation of physical processes and integration of external (top, surface, lateral) forcings that are crucial to climate scales, including interactions between land, atmosphere, and ocean; convection and microphysics; and cloud, aerosol, and radiation; and system consistency throughout all process modules. This extension inherits all WRF functionalities for numerical weather prediction while enhancing the capability for climate modeling. As such, CWRF can be applied seamlessly to weather forecast and climate prediction. The CWRF is built with a comprehensive ensemble of alternative parameterization schemes for each of the key physical processes, including surface (land, ocean), planetary boundary layer, cumulus (deep, shallow), microphysics, cloud, aerosol, and radiation, and their interactions. This facilitates the use of an optimized physics ensemble approac...

A regional climate model downscaling projection of China future climate change

Climate changes over China from the present (1990–1999) to future (2046–2055) under the A1FI (fossil fuel intensive) and A1B (balanced) emission scenarios are projected using the Regional Climate Model version 3 (RegCM3) nests with the National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM). For the present climate, RegCM3 downscaling corrects several major deficiencies in the driving CCSM, especially the wet and cold biases over the Sichuan Basin. As compared with CCSM, RegCM3 produces systematic higher spatial pattern correlation coefficients with observations for precipitation and surface air temperature except during winter. The projected future precipitation changes differ largely between CCSM and RegCM3, with strong regional and seasonal dependence. The RegCM3 downscaling produces larger regional precipitation trends (both decreases and increases) than the driving CCSM. Contrast to substantial trend differences projected by CCSM, RegCM3 produces similar precipitation spatial patterns under different scenarios except autumn. Surface air temperature is projected to consistently increase by both CCSM and RegCM3, with greater warming under A1FI than A1B. The result demonstrates that different scenarios can induce large uncertainties even with the same RCM-GCM nesting system. Largest temperature increases are projected in the Tibetan Plateau during winter and high-latitude areas in the northern China during summer under both scenarios. This indicates that high elevation and northern regions are more vulnerable to climate change. Notable discrepancies for precipitation and surface air temperature simulated by RegCM3 with the driving conditions of CCSM versus the model for interdisciplinary research on climate under the same A1B scenario further complicated the uncertainty issue. The geographic distributions for precipitation difference among various simulations are very similar between the present and future climate with very high spatial pattern correlation coefficients. The result suggests that the model present climate biases are systematically propagate into the future climate projections. The impacts of the model present biases on projected future trends are, however, highly nonlinear and regional specific, and thus cannot be simply removed by a linear method. A model with more realistic present climate simulations is anticipated to yield future climate projections with higher credibility.

A hybrid approach to improving the skills of seasonal climate outlook at the regional scale

Abstract A hybrid seasonal forecasting approach was generated by the National Centers for Environmental Prediction operational Climate Forecast System (CFS) and its nesting Climate extension of Weather Research and Forecasting (CWRF) model to improve forecasting skill over the United States. Skills for the three summers of 2011–2013 were evaluated regarding location, timing, magnitude, and frequency. Higher spatial pattern correlation coefficients showed that the hybrid approach substantially improved summer mean precipitation and 2-m temperature geographical distributions compared with the results of the CFS and CWRF models. The area mean temporal correlation coefficients demonstrated that the hybrid approach also consistently improved the timing prediction skills for both variables. In general, the smaller root mean square errors indicated that the hybrid approach reduced the magnitude of the biases for both precipitation and temperature. The greatest improvements were achieved when the individual models had similar skills. The comparison with a North American multi-model ensemble further proved the feasibility of improving real-time seasonal forecast skill by using the hybrid approach, especially for heavy rain forecasting. Based on the complementary advantages of CFS the global model and CWRF the nesting regional model, the hybrid approach showed a substantial enhancement over CFS real-time forecasts during the summer. Future works are needed for further improving the quality of the hybrid approach through CWRF’s optimized physics ensemble, which has been proven to be feasible and reliable.

Regional Climate Model Simulations of the 1998 Summer China Flood: Dependence on Initial and Lateral Boundary Conditions

The dependence of the RegCM3 (Regional Climate Model version 3) downscaling skill on initial conditions (ICs) and lateral boundary conditions (LBCs) are investigated for the 1998 summer flood along the Yangtze River Basin in China. The effect of IC uncertainties is depicted by 15 realizations starting on each consecutive day from April 1 to 15 while all ending on September 1, 1998 with identical driving LBCs, analyses are based on June, July and August simulations. The result reveals certain IC effect on precipitation for daily evolution but little for summer mean geographical distribution. In contrast, the effect of LBCs uncertainties as represented by four different reanalyses are notably larger in both daily evolution and summer mean distribution. The ensemble average among either 15 IC realizations or 4 LBC runs does not show important skill improvement over the individuals. None of the RegCM3 simulations (including the ensemble means) captured the observed main rain band along the Yangtze River Basin. This general failure suggests the need for further model physics improvement.

Regional climate model downscaling may improve the prediction of alien plant species distributions

Distributions of invasive species are commonly predicted with species distribution models that build upon the statistical relationships between observed species presence data and climate data. We used field observations, climate station data, and Maximum Entropy species distribution models for 13 invasive plant species in the United States, and then compared the models with inputs from a General Circulation Model (hereafter GCM-based models) and a downscaled Regional Climate Model (hereafter, RCM-based models).We also compared species distributions based on either GCM-based or RCM-based models for the present (1990–1999) to the future (2046–2055).RCM-based species distribution models replicated observed distributions remarkably better than GCM-based models for all invasive species under the current climate. This was shown for the presence locations of the species, and by using four common statistical metrics to compare modeled distributions. For two widespread invasive taxa (Bromus tectorum or cheatgrass, and Tamarix spp. or tamarisk), GCM-based models failed miserably to reproduce observed species distributions. In contrast, RCM-based species distribution models closely matched observations. Future species distributions may be significantly affected by using GCM-based inputs. Because invasive plants species often show high resilience and low rates of local extinction, RCM-based species distribution models may perform better than GCM-based species distribution models for planning containment programs for invasive species.

Sensitivity of CWRF simulations of the China 1998 summer flood to cumulus parameterizations

Better understanding the dynamics of the East Asian monsoon system is essential to address its climate variability and predictability. Regional climate models are useful tools for this endeavor, but require a rigorous evaluation to first establish a suite of physical parameterizations that best simulate observations. To this end, the present study focuses on the CWRF (Climate extension of WRF) simulation of the 1998 summer flood over east China and its sensitivity to cumulus parameterizations on CWRF performance. The CWRF using the Kain-Fritsch and Grell-Devenyi cumulus schemes both capture the observed major characteristics of geographic distributions and daily variations of precipitation, indicating a high credibility in downscaling the monsoon. Important regional differences, however, are simulated by the two schemes. The Kain-Fritsch scheme produces the better precipitation patterns with smaller root-mean-square errors and higher temporal correlation coefficients, while overestimating the magnitude and coverage. In contrast, the Grell-Devenyi ensemble scheme, using equal weights on all closure members, overall underestimates rainfall amount, suggesting for future improvement with varying weights depending on climate regimes.

CWRF simulations of the China 1991 and 1998 summer floods

The capability of the Climate extension of the Weather Research and Forecasting (CWRF) model in simulating the 1991 and 1998 summer floods in China is evaluated with 4-month continuous integrations as driven by the NCEP/NCAR observational reanalysis. It is shown that CWRF has a pronounced downscaling skill, capturing the key characteristics in the spatial patterns and temporal evolutions of precipitation in both severe anomalous monsoon cases. The result gives a high perspective for future CWRF applications in understanding and predicting China monsoon variability.

Numerical simulation of Summer 2003 climate in China region using RegCM3

China is a country with complex topography, land surface conditions, coastlines with the world highest plateau in its west and the largest ocean at its east, and with large contribution from mesoscale phenomena, such as the mei-yu frontal systems and tropical storms. To study the regional climate in such a region, a highly resolved regional climate model (RegCM) has been recently developed at the International Pacific Research Center (IPRC). The distinct features of this model include direct feedback of cumulus detrained cloud ice and cloud water into the grid-resolved quantities; the effect of cloud buoyancy on turbulence production with mixed-ice phase clouds; an explicit coupling between the cloud microphysics and radiation via cloud properties; an explicit coupling between land surface and radiation via surface albedo, direct and diffuse radiation fluxes; and the effect of frictionally generated dissipative heating. The performance of RegCM3 is demonstrated by its simulation of the 2003 summer extreme climate event over the whole China region including Tibetan Plateau. There have not had so many studies about this region on this regard. With the use of the NCEP Reanalysis 2 data provided by the NOAA-CIRES Climate Diagnostic Center, Boulder, Colorado, USA, from their Web site at http://www.cdc.noaa.gov/, which is available at 6hr intervals with a resolution of 2.5°×2.5°, as both the initial and lateral boundary conditions, the model was integrated from 1 May to 31 August 2003 with a resolution of 60km×60km covering the area of 15°-55°N, 70°-140°E. It is demonstrated that the RegCM3 has a pronounced rainfall downscaling scale, producing more realistic regional details and overall smaller biases than the driving reanalysis data. The model simulated realistically not only the temporal evolution of the area-averaged precipitation and the monthly mean precipitation spatial pattern but also the daily precipitation intensity distribution.