Modelling the Gross Primary Productivity of West Africa with the Regional Biomass Model RBM+, using optimized 250 m MODIS FPAR and fractional vegetation cover information

Global warming associated with climate change is one of the greatest challenges of today’s world. Increasing emissions of the greenhouse gas CO₂ are considered as a major contributing factor to global warming. One regulating factor of CO₂ exchange between atmosphere and land surface is vegetation. Measurements of land cover changes in combination with modelling the Gross Primary Productivity (GPP) can contribute to determine important sources and sinks of CO₂.The aim of this study is to accurately model the GPP for a region in West Africa with a spatial resolution of 250 m, and the differentiation of GPP based on woody and herbaceous vegetation. For this purpose, the Regional Biomass Model (RBM) was applied, which is based on a Light Use Efficiency (LUE) approach. The focus was on the spatial enhancement of the RBM from the original 1000–250 m spatial resolution (RBM+). The adaptation to the 250 m scale included the modification of two main input parameters: (1) the fraction of absorbed Photosynthetically Active Radiation (FPAR) based on the 1000 m MODIS MOD15A2 FPAR product which was downscaled to 250 m using MODIS NDVI time series; (2) the fractional cover of woody and herbaceous vegetation, which was improved by using a multi-scale approach. For validation and regional adjustments of GPP and the input parameters, in situ data from a climate station and eddy covariance measurements were integrated.The results of this approach show that the input parameters could be improved significantly: downscaling considerably reduces data gaps of the original FPAR product and the improved dataset differed less than 5.0% from the original data for cloud free regions. The RMSE of the fractional vegetation cover varied between 5.1 and 12.7%. Modelled GPP showed a slight overestimation in comparison to eddy covariance measurements. The in situ data was exceeded by 8.8% for 2005 and by 2.0% for 2006. The model results were converted to NPP and also agreed well with previous NPP measurements reported from different studies. Altogether a high accuracy and suitability of the regionally adjusted and downscaled model RBM+ can be concluded. The differentiation between vegetation growth forms allows a separation of long-term and short-term carbon storage based on woody and herbaceous vegetation, respectively.     

Estimation of potential evapotranspiration over the Yellow River basin: reference crop evaporation or Shuttleworth–Wallace?

Potential evapotranspiration (PET) is a key input to hydrological models. Its estimation has often been via the Penman–Monteith (P–M) equation, most recently in the form of an estimate of reference evapotranspiration (RET) as recommended by FAO‐56. In this paper the Shuttleworth–Wallace (S–W) model is implemented to estimate PET directly in a form that recognizes vegetation diversity and temporal change without reference to experimental measurements and without calibration. The threshold values of vegetation parameters are drawn from the literature based on the International Geosphere–Biosphere Programme land cover classification. The spatial and temporal variation of the LAI of vegetation is derived from the composite NOAA‐AVHRR normalized difference vegetation index (NDVI) using a method based on the SiB2 model, and the Climate Research Unit database is used to provide the required meteorological data. All these data inputs are publicly and globally available. Consequently, the implementation of the S–W model developed in this study is applicable at the global scale, an essential requirement if it is to be applied in data‐poor or ungauged large basins. A comparison is made between the FAO‐56 method and the S–W model when applied to the Yellow River basin for the whole of the last century. The resulting estimates of RET and PET and their association with vegetation types and leaf area index (LAI) are examined over the whole basin both annual and monthly and at six specific points. The effect of NDVI on the PET estimate is further evaluated by replacing the monthly NDVI product with the 10‐day product. Multiple regression relationships between monthly PET, RET, LAI, and climatic variables are explored for categories of vegetation types. The estimated RET is a good climatic index that adequately reflects the temporal change and spatial distribution of climate over the basin, but the PET estimated using the S–W model not only reflects the changes in climate, but also the vegetation distribution and the development of vegetation in response to climate. Although good statistical relationships can be established between PET, RET and/or climatic variables, applying these relationships likely will result in large errors because of the strong non‐linearity and scatter between the PET and the LAI of vegetation. It is concluded that use of the implementation of the S–W model described in this study results in a physically sound estimate of PET that accounts for changing land surface conditions. Copyright © 2006 John Wiley & Sons, Ltd.     

刍议《重庆历史地图集》第二卷的编制

以《重庆历史地图集》第二卷编制的具体情况为例,对图集的开本设计、内容结构设计、封面和版式设计、整体设计、创新源,以及图集编制取得的经验进行了论述,为以后类似图集的编制提供参考。     

The Effects of Land Cover Change on Regional Climate over the Eastern Part of Northwest China

A regional climate model(Reg CM4) is employed to investigate the impacts of land use/cover change(LUCC) on the climate over the eastern part of Northwest China(ENW) in the periods of 2001 and 2011. The results indicated that the LUCC in ENW, which was characterized by desert retreat, reforestation, and farmland expansion, led to significant local changes in surface air temperature(within ~0.3°C) and slight regional changes in precipitation(within ~15%) in summer. In the desert retreat area, the net absorbed shortwave radiation had a greater influence than evaporative cooling, leading to increases in the daily mean and maximum temperature. Besides, the daily mean and maximum temperatures increased in the reforestation area but decreased in the farmland expansion area. As surface albedo showed no significant change in these regions, the temperature increase in the reforestation area can be attributed to a decrease in evaporation, while the opposite effect appears to have been the case in the farmland expansion area.     

Evaluating the economic damage of climate change on global coral reefs

This paper evaluates the global economic damage arising from the effects of climate change and associated carbon dioxide concentrations on the loss of coral reefs. We do this by first estimating the effects of sea surface temperature and carbon dioxide concentrations on coral cover. We develop a statistical relationship between coral coverage and sea surface temperature that indicates that the effects are dependent on the temperature range. For example, we find that increasing sea surface temperature causes coral coverage to decrease when sea surface temperature is higher than 26.85 °C, with the estimated reduction being 2.3% when sea surface temperature increases by 1%. In addition, we find that a 1% carbon dioxide increase induces a 0.6% reduction in global coral coverage. We also estimate the resultant loss in economic value based on a meta-analysis of the recreational and commercial value of reef coverage and a crude proportional approach for other value factors. The meta-analysis shows that the coral reef value decreases by 3.8% when coral cover falls by 1%. By combining these two steps we find that the lost value in terms of the global coral reef value under climate change scenarios ranges from US$3.95 to US$23.78 billion annually.     

The total operating characteristic to measure diagnostic ability for multiple thresholds

The relative operating characteristic (ROC) is a popular statistical method to measure the association between observed and diagnosed presence of a characteristic. The diagnosis of presence or absence depends on whether the value of an index variable is above a threshold. ROC considers multiple possible thresholds. Each threshold generates a two-by-two contingency table, which contains four central entries: hits, misses, false alarms, and correct rejections. ROC reveals for each threshold only two ratios, hits/(hits + misses) and false alarms/(false alarms + correct rejections). This article introduces the total operating characteristic (TOC), which shows the total information in the contingency table for each threshold. TOC maintains desirable properties of ROC, while TOC reveals strictly more information than ROC in a manner that makes TOC more useful than ROC. We illustrate the concepts with an application to land change science.     

Thermodynamic properties of snow cover on sea ice during the austral summer in Prydz Bay,East Antarctica

The thermodynamic properties of snow cover on sea ice play a key role in the ice-ocean-atmosphere system and have been a focus of recent scientific research. In this study, we investigated the thermodynamic properties of snow cover on sea ice in the Nella Fjord, Prydz Bay, East Antarctica(69°20′S, 76°07′E), near the Chinese Antarctic Zhongshan Station. Our observations were carried out during the 29th Chinese National Antarctic Research Expedition. We found that the vertical temperature profile of snow cover changed considerably in response to changes in air temperature and solar radiation during the summer. Associated with the changes in the temperature profile were fluctuations in the temperature gradient within the upper 10 cm of the snow cover. Results of previous research have shown that the thermal conductivity of snow is strongly correlated with snow density. To calculate the thermal conductivity in this study, we measured densities in three snow pits. The calculated thermal conductivity ranged from 0.258–0.569 W?m-1?K-1. We present these datasets to show how involved parameters changed, and to contribute to a better understanding of melting processes in the snow cover on sea ice.     

大伙房库区近30年来植被覆盖变化分析

根据像元二分模型原理,利用1983年、2000年、2011年大伙房库区遥感影像数据提取植被覆盖遥感信息,结合植被指数计算植被覆盖度,分析比较大伙房库区不同时期植被覆盖的变化,研究大伙房库区这三个时期植被覆盖动态变化规律,为大伙房库区的生态建设和可持续发展提供决策支持。结果显示:1近30年以来,大伙房库区植被覆盖等级分布不均衡,高植被覆盖区过分集中在北部地带,西部则多为低植被覆盖区;2大伙房库区高植被覆盖面积在减少、低植被覆盖面积在增加;3大伙房库区植被覆盖总面积在下降,库区的生态环境已经遭到了破坏;4政策建议:加强监测与监管力度,合理开发利用矿产资源,积极响应国家"退耕还林、退耕还草"号召。     

A Dipole Pattern of Summer Precipitation over Mid-high Latitude Asia and Related Snow Cover Anomalies in the Preceding Spring

A dipole pattern of summer precipitation over the mid-high latitudes of Asia, which is characterized by opposing summer precipitation variations between the Mongolian and Northeast China （MNC） region and the West Siberian Plain （WSP）, is found to be clear and stable on both interdecadal and interannual scales during 1981- 2011. Spring snow cover anomalies over a small region within the WSP and the Heilongjiang River （HR） region are closely related to the variation of this dipole mode during the subsequent summer, and they can therefore be considered as forecasting factors. Our statistical results imply a potential process explaining the relationship between the spring snow anomalies and the summer rainfall dipole. Corresponding to the snow anomalies, Rossby waves propagate along a path from the WSP region, via the Mongolian Plateau, to the Stanovoy Range during summer. At the same time, Rossby-wave energy divergences and convergences along this path maintain and reinforce an anomalous cyclone and anticyclone pairing over the Asian continent, which is significantly linked to opposite summer precipitation anomalies between the MNC and WSP regions. Numerical experiments are need- ed to further confirm the above conjecture and demonstrate the detailed physical mechanisms linking the spring snow cover anomalies and summer precipitation dipole.     

Assessing integration of intensity,polarimetric scattering,interferometric coherence and spatial texture metrics in PALSAR-derived land cover classification

Synthetic aperture radar (SAR) is an important alternative to optical remote sensing due to its ability to acquire data regardless of weather conditions and day/night cycle. The Phased Array type L-band SAR (PALSAR) onboard the Advanced Land Observing Satellite (ALOS) provided new opportunities for vegetation and land cover mapping. Most previous studies employing PALSAR investigated the use of one or two feature types (e.g. intensity, coherence); however, little effort has been devoted to assessing the simultaneous integration of multiple types of features. In this study, we bridged this gap by evaluating the potential of using numerous metrics expressing four feature types: intensity, polarimetric scattering, interferometric coherence and spatial texture. Our case study was conducted in Central New York State, USA using multitemporal PALSAR imagery from 2010. The land cover classification implemented an ensemble learning algorithm, namely random forest. Accuracies of each classified map produced from different combinations of features were assessed on a pixel-by-pixel basis using validation data obtained from a stratified random sample. Among the different combinations of feature types evaluated, intensity was the most indispensable because intensity was included in all of the highest accuracy scenarios. However, relative to using only intensity metrics, combining all four feature types increased overall accuracy by 7%. Producer’s and user’s accuracies of the four vegetation classes improved considerably for the best performing combination of features when compared to classifications using only a single feature type.