Jianping Tang

Improvement of aerosol optical depth retrieval using visibility data in China during the past 50 years

Horizontal visibility and water vapor pressure data from 483 stations in China from 1960 to 2009 were used to inverse aerosol optical depth (AOD) using a new series of parameters, which were revised for each station using the polybasic nonlinear regression method based on monthly Multiangle Imaging Spectroradiometer (MISR) AOD data during 2001–2005. Monthly AOD retrievals from 2006 to 2009 using the new parameters were compared with MISR AOD in the same period. AOD retrieved with the new parameters can capture the extreme values better than the inversion result with the original parameters, and the root-mean-square error between retrieval and MISR AOD reached the minimum of 0.047 in northwest China and the maximum of 0.102 in the Huang–Huai River Basin, respectively. The spatial distribution and seasonal features of monthly AOD from 1960 to 2009 in China were also analyzed. The monthly AOD in China for past 50 years, from 1960 to 2009, exhibited an increasing trend, especially during 1960–1985, with a linear rate of increase of 0.004/year. No distinct trend can be found for AOD from 1985 to 1995; then it increased obviously from 1996 to 2009 with an annual rate of 0.002. Seasonal change in AOD showed that it reached a maximum value in summer with the average value between 0.34 and 0.36 for the whole China, while a minimum value was reached in winter with a mean value between 0.2 and 0.22. It is noted that the aerosol vertical profile was a sensitive factor to the inversion result. The root-mean-square error using Goddard Chemistry Aerosol Radiation and Transport aerosol profiles was increased 1.9 to 5.7 times than using the traditional three-segment profile in northwest, southwest, northeast, and northern China, which meant that the retrieval AOD was sensitive to aerosol vertical profile in these regions; at the same time, the root-mean-square error was decreased 1.13 to 1.37 times in other regions.

Effects of the land-surface heterogeneities in temperature and moisture from the ''combined approach'' on regional climate: a sensitivity study

In order to better understand the land–atmosphere interactions and increase the predictability of climate models, it is very important to investigate the effects of land-surface heterogeneities, in which the temperature and moisture heterogeneities are very significant. In this paper, the land-surface scheme BATS [Dickinson, R.E., Henderson-Sellers, A., Kennedy, P.J., Wilson, M.F., 1993. Biosphere /Atmosphere Transfer Scheme (BATS) Version 1e as Coupled to the NCAR Community Climate Model. NCAR Tech. Note TN-387+STR, National Center for Atmospheric Research, Boulder, CO], in the NCAR regional climate model RegCM2, was treated with a ‘‘combined approach’’ that is computationally effective to represent land-surface heterogeneities in temperature and moisture, and was tested by using real data of China during the summer monsoon in 1991 as initial and boundary conditions. Different from the results of the off-line simulations for warm season in Giorgi [Mon. Weather Rev. 125 (1997b) 1900], as for temperature, we used a cosine probability density function (PDF), which is more effective in computation and different from the linear PDF applied by Giorgi [Mon. Weather Rev. 125 (1997a) 1885]; we can see that the summer monsoon climate is generally sensitive to the temperature heterogeneity (e.g., precipitation is sensitive to the temperature heterogeneity). Similar to the results in Giorgi [Mon. Weather Rev. 125 (1997b) 1900], the regional climate seems to be very sensitive to the moisture heterogeneity, which shows a regularity as changing with the heterogeneity, i.e., with the heterogeneity increasing, the mean sensible heat flux is generally increased, while the mean latent heat flux is generally decreased. So, the capability of simulation for summer monsoon climate may be improved via the appropriate representation of the heterogeneities in temperature and moisture. In addition, other results reveal the limitations of off-line experiments, and therefore the coupling of the land-surface scheme (with the inclusion of heterogeneity representation) to the atmospheric model is necessary for the study on land–atmosphere interactions. D 2002 Elsevier Science B.V. All rights reserved.

Multimodel ensemble projection of precipitation in eastern China under A1B emission scenario

As part of the Regional Climate Model Intercomparison Project for Asia, future precipitation projection in China is constructed using five regional climate models (RCMs) driven by the same global climate model (GCM) of European Centre/Hamburg version 5. The simulations cover both the control climate (1978–2000) and future projection (2041–2070) under the Intergovernmental Panel on Climate Change emission scenario A1B. For the control climate, the RCMs have an advantage over the driving GCM in reproducing the summer mean precipitation distribution and the annual cycle. The biases in simulating summer precipitation mainly are caused by the deficiencies in reproducing the low-level circulation, such as the western Pacific subtropical high. In addition, large inter-RCM differences exist in the summer precipitation simulations. For the future climate, consistent and inconsistent changes in precipitation between the driving GCM and the nested RCMs are observed. Similar changes in summer precipitation are projected by RCMs over western China, but model behaviors are quite different over eastern China, which is dominated by the Asian monsoon system. The inter-RCM difference of rainfall changes is more pronounced in spring over eastern China. North China and the southern part of South China are very likely to experience less summer rainfall in multi-RCM mean (MRM) projection, while limited credibility in increased summer rainfall MRM projection over the lower reaches of the Yangtze River Basin. The inter-RCM variability is the main contributor to the total uncertainty for the lower reaches of the Yangtze River Basin and South China during 2041–2060, while lowest for Northeast China, being less than 40%.

Future climate projection under IPCC A1B scenario in the source region of Yellow River with complex topography using RegCM3

Located on the Tibetan Plateau, the source region of Yellow River has experienced remarkable climate change over past a few decades, which affects the regional ecosystem, agricultural development, and water availability. In this paper, high-resolution RegCM3 driven by ECHAM5 is applied to generate both control climate for 1980-2000 and regional climate projections for the 21st century (2010-2098) under the Intergovernmental Panel on Climate Change (IPCC) A1B emission scenario. For control climate, RegCM3 can well reproduce the spatial patterns of precipitation and surface air temperature with more detailed representation of fine scale topography. Wet and cold biases are produced in the simulation, but overall improvement by RegCM3 is evident compared to the driving global climate model (GCM) of ECHAM5. In the future projection, the model demonstrates significant warming over the whole analysis domain. Precipitation on the other hand shows mixed signals of reduction and increase over simulation domain, while the areas of precipitation reduction extend with increasing integration time and finally covermost parts of the domain at the end of 21st century. As projection time increases, high altitude region will experience more precipitation reduction in summer and less reduction or even increase in winter. The winter warming at the high elevation area gets more evident than that at the low elevation area, which may be due to the snow feedback. Analyzing the change of probability distributions of surface climate, it can be concluded that the frequency of heavy precipitation in winter tends to increase with time indicating more extreme precipitation events in the future. The spectrum of temperature probability density functions (PDFs) moves toward higher end.

A numerical simulation of aerosols’ direct effects on tropopause height

The direct effects of sulfate aerosol, dust aerosol, carbonaceous aerosol, and total combined aerosols on the tropopause height are simulated with the Community Atmospheric Model version 3.1 (CAM3.1). A decrease of global mean tropopause height induced by sulfate, carbonaceous aerosol, and total combined aerosols is found, and a tropopause height increase is induced by dust aerosol. Sulfate aerosol decreases the tropospheric temperature and increases the stratospheric temperature. These effects cause a decrease in the height of the tropopause. In contrast, carbonaceous and total combined aerosols increase both the tropospheric and the stratospheric temperatures, and they also cause a decrease in the height of the tropopause. The changes in the tropopause height show highly statistically significant correlations with the changes in the tropospheric and stratospheric temperatures. The changes in the tropospheric and stratospheric temperatures are related to the changes in the radiative heat rate, cloud cover, and latent heat, but none of these factors absolutely dominate the temperature change.

Impact of spectral nudging on regional climate simulation over CORDEX East Asia using WRF

In this study, the impact of the spectral nudging method on regional climate simulation over the Coordinated Regional Climate Downscaling Experiment East Asia (CORDEX-EA) region is investigated using the Weather Research and Forecasting model (WRF). Driven by the ERA-Interim reanalysis, five continuous simulations covering 1989–2007 are conducted by the WRF model, in which four runs adopt the interior spectral nudging with different wavenumbers, nudging variables and nudging coefficients. Model validation shows that WRF has the ability to simulate spatial distributions and temporal variations of the surface climate (air temperature and precipitation) over CORDEX-EA domain. Comparably the spectral nudging technique is effective in improving the model’s skill in the following aspects: (1), the simulated biases and root mean square errors of annual mean temperature and precipitation are obviously reduced. The SN3-UVT (spectral nudging with wavenumber 3 in both zonal and meridional directions applied to U, V and T) and SN6 (spectral nudging with wavenumber 6 in both zonal and meridional directions applied to U and V) experiments give the best simulations for temperature and precipitation respectively. The inter-annual and seasonal variances produced by the SN experiments are also closer to the ERA-Interim observation. (2), the application of spectral nudging in WRF is helpful for simulating the extreme temperature and precipitation, and the SN3-UVT simulation shows a clear advantage over the other simulations in depicting both the spatial distributions and inter-annual variances of temperature and precipitation extremes. With the spectral nudging, WRF is able to preserve the variability in the large scale climate information, and therefore adjust the temperature and precipitation variabilities toward the observation.

Regional integrated environmental modeling system: development and application

The demand for high-confidence regional climate change scenarios is increasing. It is therefore vitally important to better understand the behavior of Earth’s climate system on regional scale and advance the knowledge of regional responses to global climate. With their ability to represent meso-scale forcings, such as coastline, complex topography, anthropogenic aerosols and land cover/use changes, Regional Climate Models (RCMs) are developed and used worldwide to investigate the effects of the above-mentioned meso-scale forcings on the local circulations that regulate the regional distribution of climatic variables. Considering the complexity of Asian Monsoon system, which is not only a physical process but also modulated by the interaction among physical, biological, chemical and social processes, a modeling framework Regional Integrated Environmental Modeling System (RIEMS) was proposed, developed and well tested before it was widely used in regional climate studies in the East Asia monsoon region.

Heat Waves in China: Definitions, Leading Patterns, and Connections to Large-Scale Atmospheric Circulation and SSTs

Based on the daily maximum temperatures (Tmax) from 587 surface observation stations in China during 1959–2013, heat waves are detected using both absolute and relative definitions. The spatiotemporal variations of heat wave occurrence/duration/amplitude are compared between the two definitions. Considering the significant differences in regional climatology, relative threshold is more meaningful to detect the local extremes. By utilizing the empirical orthogonal function, the integral index heat wave total intensity is decomposed into three dominant modes: interdecadal (ID), interannual-tripole (IA-TR), and interannual-dipole (IA-DP) modes. The ID mode shows uniform anomalies over the whole China, with the maximum in north, and its corresponding time series depict notable interdecadal variations with a turning point around mid-1990s. The IA-DP mode exhibits opposite-signed anomalies over north and south China. The IA-TR mode shows an anomalous tripole pattern with negative anomalies over central China and positive anomalies over north and south China in its positive phase. Both the IA-DP and IA-TR patterns are more obvious since mid-1990s with mainly year-to-year variations before that. All the three modes are controlled by anomalous high-pressure systems, which are accompanied by local-scale dry land conditions. The diabatic heating associated with anomalous convective activities over tropical western Pacific triggers Rossby wave trains propagating northward along the East Asia, which causes abnormal heat waves through descending motion over the high-pressure nodes. In turn, the severe convections are generated by enhanced Walker circulation in the tropical Pacific due to warming and/or cooling sea surface temperature (SST) anomalies in the tropical western and eastern Pacific, respectively.

Regional heatwaves in china: a cluster analysis

With the consideration of spatial extension of heatwave events, two kind of regional heatwaves using absolute and relative thresholds, namely RHWs-A and RHWs-R, are investigated during 1959–2013. The temperature data is derived from the daily maximum temperatures (DMTs) of 587 stations in China. Totally 298 RHWs-A and 374 RHWs-R are identified during the past 55 years, and both of them are growing more frequent since the mid-1980s. By utilizing the cluster analysis, several typical spatial distributions of RHWs-A/RHWs-R are obtained. For RHWs-A, there are three clusters covering the southeastern, northwestern China and the lower reaches of Yangtze River, of which the southeastern cluster groups the most heatwaves. For RHWs-R, there are seven clusters distributed throughout the whole regions of China. The clusters in the northwestern and northeastern China are more stable than others for both RHWs-A and RHWs-R, and the northern clusters are of larger intensity than that of the southern ones. All RHWs-A/RHWs-R are accompanied by the anomalous high systems along with the reduced soil moisture. The southern clusters are controlled by Northwestern Pacific subtropical high (WPSH), and the northern ones are influenced by the mid-latitude high systems. The influences of atmospheric circulations and soil moisture on regional heatwaves are further demonstrated by two case analyses of the severe RHW-A in 2003 and the RHW-R in 2013.

On the Determination and Characteristics of Effective Roughness Length for Heterogeneous Terrain

A new method is proposed for the effective roughness length (ERL) in heterogeneous terrain based on the principle of equalisation of momentum or heat fluxes calculated by the drag coefficient parameterization scheme used in the ECMWF numerical model. Compared with the area-weighted logarithmically averaged ERL (drag coefficient), the newly calculated ERL (drag coefficient) is about 40% (16%) larger with a roughness step of 2.3. These differences reach their maximum values when the ratio of smooth to rough surface is 60% to 40%. Since the determination by this method is not sensitive to the atmospheric stratification, it is suitable for use in climate models.