Because land cover plays an important role in global climate change studies, assessing the agreemen among different land cover products is critical. Significan discrepancies have been reported among satellite-derived land cover products, especially at the regional scale. Different classification schemes are a key obstacle to the comparison of products and are considered the main factor behind the disagreement among the different products Using a feature-based overlap metric, we investigated the degree of spatial agreement and quantified the overall and class-specific agreement among the Moderate Resolution Imaging Spectoradiometer (MODIS), Global Land Cover 2000 (GLC2000), and the National Land Cover/Use Data-sets (NLCD) products, and the author assessed the products by ground reference data at the regional scale over China. The areas with a low degree of agreement mostly occurred in heterogeneous terrain and transition zones while the areas with a high degree of agreement occurred in major plains and areas with homogeneous vegetation The overall agreement of the MODIS and GLC2000 products was 50.8% and 52.9%, and the overall accuracy was 50.3% and 41.9%, respectively. Class-specific agreement or accuracy varied significantly. The high-agreemen classes are water, grassland, cropland, snow and ice, and bare areas, whereas classes with low agreement are shru-bland and wetland in both MODIS and GLC2000. These characteristics of spatial patterns and quantitative agreement could be partly explained by the complex landscapes mixed vegetation, low separability of spectro-temporal-texture signals, and coarse pixels. The differences of class definition among different the classification schemes also affects the agreement. Each product had its advantages and limitations, but neither the overall accuracy nor the class-specific accuracy could meet the requirements of climate modeling.
In this study,a new parameter optimization method was used to investigate the expansion of conditional nonlinear optimal perturbation (CNOP) in a land surface model (LSM) using long-term enhanced field observations at Tongyu station in Jilin Province,China,combined with a sophisticated LSM (common land model,CoLM).Tongyu station is a reference site of the international Coordinated Energy and Water Cycle Observations Project (CEOP) that has studied semiarid regions that have undergone desertification,salination,and degradation since late 1960s.In this study,three key land-surface parameters,namely,soil color,proportion of sand or clay in soil,and leaf-area index were chosen as parameters to be optimized.Our study comprised three experiments:First,a single-parameter optimization was performed,while the second and third experiments performed triple-and six-parameter optimizations,respectively.Notable improvements in simulating sensible heat flux (SH),latent heat flux (LH),soil temperature (TS),and moisture (MS) at shallow layers were achieved using the optimized parameters.The multiple-parameter optimization experiments performed better than the single-parameter experminent.All results demonstrate that the CNOP method can be used to optimize expanded parameters in an LSM.Moreover,clear mathematical meaning,simple design structure,and rapid computability give this method great potential for further application to parameter optimization in LSMs.
Enhanced observational meteorological elements,energy fluxes,and the concentration of dust aerosols collected from the Semi-Arid Climate Observatory and Laboratory(SACOL) during a typical dust storm period in March 2010 at Lanzhou were used in this paper to investigate the impact of dust aerosols on near surface atmospheric variables and energy budgets.The results show that the entire dust storm event was associated with high wind velocities and decreasing air pressure,and the air changed from cold and wet to warm and dry and then recovered to its initial state.The response of energy fluxes occurred behind meteorological elements.At high dust concentration periods,the net radiation was significantly less in the daytime and higher at night,while the heat fluxes displayed the same trend,indicating the weakening of the land-atmosphere energy exchange.The results can be used to provide verification for numerical model results in semi-arid areas.
The temperature thresholds and timings of the 24 climatic Solar Terms in China are determined from a homogenized dataset of the surface air temperature recorded at 549 meteorological stations for the period 1960-2008 employing the ensemble empirical mode decomposition method.Changes in the mean temperature and timing of the climatic solar terms are illustrated.The results show that in terms of the mean situation over China,the number of cold days such as those of Slight Cold and Great Cold has decreased,especially by 56.8% for Great Cold in the last 10 years(1998-2007) compared with in the 1960s.The number of hot days like those of Great Heat has increased by 81.4% in the last 10 years compared with in the 1960s.The timings of the climatic Solar Terms during the warming period(around spring) in the seasonal cycle have advanced significantly by more than 6 d,especially by 15 d for Rain Water,while those during the cooling period(around autumn) have delayed significantly by 5-6 d.These characteristics are mainly due to a warming shift of the whole seasonal cycle under global warming.However,the warming shift affects the different Solar Terms to various extents,more prominently in the spring than in the autumn.The warming tendencies for Rain Water,the Beginning of Spring,and the Waking of Insects are the largest,2.43?C,2.37?C,and 2.21?C,respectively,for the period 1961-2007 in China as a whole.Four particular phenology-related climatic Solar Terms,namely the Waking of Insects,Pure Brightness,Grain Full,and Grain in Ear,are found to have advanced almost everywhere.In semi-arid zones in northern China,advances of the timings of these four climatic Solar Terms are significant,12-16,4-8,4-8,and 8-12 d,respectively,for the period 1961-2007.These quantitative results provide a scientific base for climate change adaptation,especially in terms of agricultural planning and energy-saving management throughout a year.
The long-term change of the whole spectra of precipitation intensity in China is examined using observed daily data recorded at 477 surface stations for the period from 1961 to 2008. The results show a spatially coherent decrease of trace precipitation despite different reduction magnitudes among the regions. For measurable precipitation, significant regional and seasonal characteristics are observed. In autumn, the whole measurable precipitation decreased over Eastern China (east of 98°E). In summer and winter, a significant increase of heavy precipitation and decrease of light precipitation are detected south of Eastern China. In Western China, measurable precipitation is found to have increased in all four seasons. Composite analysis reveals a quasi-linear relationship between increasing surface temperature and precipitation on a global scale. The responses of precipitation at different intensities to the increased temperature are distinct, with a significant spectra-shifting from light to heavy precipitation. Compared with precipitation over the ocean, the amplification of heavy precipitation over land is relatively less, most likely constrained by the limited water supply. The response of regional precipitation to global warming shows greater uncertainties compared with those on the global scale, perhaps due to interference by more complex topography and land cover, as well as human activities, among other factors.
Trends in the frequencies of four temperature extremes (the occurrence of warm days, cold days, warm nights and cold nights) with respect to a modulated annual cycle (MAC), and those associated exclusively with weather-intraseasonal fluctuations (WIF) in eastern China were investigated based on an updated homogenized daily maximum and minimum temperature dataset for 1960–2008. The Ensemble Empirical Mode Decomposition (EEMD) method was used to isolate the WIF, MAC, and longer-term components from the temperature series. The annual, winter and summer occurrences of warm (cold) nights were found to have increased (decreased) significantly almost everywhere, while those of warm (cold) days have increased (decreased) in northern China (north of 40°N). However, the four temperature extremes associated exclusively with WIF for winter have decreased almost everywhere, while those for summer have decreased in the north but increased in the south. These characteristics agree with changes in the amplitude of WIF. In particular, winter WIF of maximum temperature tended to weaken almost everywhere, especially in eastern coastal areas (by 10%–20%); summer WIF tended to intensify in southern China by 10%–20%. It is notable that in northern China, the occurrence of warm days has increased, even where that associated with WIF has decreased significantly. This suggests that the recent increasing frequency of warm extremes is due to a considerable rise in the mean temperature level, which surpasses the effect of the weakening weather fluctuations in northern China.
