Gensuo Jia

Circumpolar Arctic Tundra Vegetation Change Is Linked to Sea Ice Decline

Abstract Linkages between diminishing Arctic sea ice and changes in Arctic terrestrial ecosystems have not been previously demonstrated. Here, the authors use a newly available Arctic Normalized Difference Vegetation Index (NDVI) dataset (a measure of vegetation photosynthetic capacity) to document coherent temporal relationships between near-coastal sea ice, summer tundra land surface temperatures, and vegetation productivity. The authors find that, during the period of satellite observations (1982–2008), sea ice within 50 km of the coast during the period of early summer ice breakup declined an average of 25% for the Arctic as a whole, with much larger changes in the East Siberian Sea to Chukchi Sea sectors (>44% decline). The changes in sea ice conditions are most directly relevant and have the strongest effect on the villages and ecosystems immediately adjacent to the coast, but the terrestrial effects of sea ice changes also extend far inland. Low-elevation (<300 m) tundra summer land temperatures, a...

Nested high-resolution modeling of the impact of urbanization on regional climate in three vast urban agglomerations in China

[1] In this paper, the Weather Research and Forecasting Model, coupled to the Urban Canopy Model, is employed to simulate the impact of urbanization on the regional climate over three vast city agglomerations in China. Based on high-resolution land use and land cover data, two scenarios are designed to represent the nonurban and current urban land use distributions. By comparing the results of two nested, high-resolution numerical experiments, the spatial and temporal changes on surface air temperature, heat stress index, surface energy budget, and precipitation due to urbanization are analyzed and quantified. Urban expansion increases the surface air temperature in urban areas by about 1C, and this climatic forcing of urbanization on temperature is more pronounced in summer and nighttime than other seasons and daytime. The heat stress intensity, which reflects the combined effects of temperature and humidity, is enhanced by about 0.5 units in urban areas. The regional incoming solar radiation increases after urban expansion, which may be caused by the reduction of cloud fraction. The increased temperature and roughness of the urban surface lead to enhanced convergence. Meanwhile, the planetary boundary layer is deepened, and water vapor is mixed more evenly in the lower atmosphere. The deficit of water vapor leads to less convective available potential energy and more convective inhibition energy. Finally, these combined effects may reduce the rainfall amount over urban areas, mainly in summer, and change the regional precipitation pattern to a certain extent.

Spatial and temporal patterns of greenness on the Yamal Peninsula, Russia: interactions of ecological and social factors affecting the Arctic normalized difference vegetation index

The causes of a greening trend detected in the Arctic using the normalized difference vegetation index (NDVI) are still poorly understood. Changes in NDVI are a result of multiple ecological and social factors that affect tundra net primary productivity. Here we use a 25 year time series of AVHRR-derived NDVI data (AVHRR: advanced very high resolution radiometer), climate analysis, a global geographic information database and ground-based studies to examine the spatial and temporal patterns of vegetation greenness on the Yamal Peninsula, Russia. We assess the effects of climate change, gas-field development, reindeer grazing and permafrost degradation. In contrast to the case for Arctic North America, there has not been a significant trend in summer temperature or NDVI, and much of the pattern of NDVI in this region is due to disturbances. There has been a 37% change in early-summer coastal sea-ice concentration, a 4% increase in summer land temperatures and a 7% change in the average time-integrated NDVI over the length of the satellite observations. Gas-field infrastructure is not currently extensive enough to affect regional NDVI patterns. The effect of reindeer is difficult to quantitatively assess because of the lack of control areas where reindeer are excluded. Many of the greenest landscapes on the Yamal are associated with landslides and drainage networks that have resulted from ongoing rapid permafrost degradation. A warming climate and enhanced winter snow are likely to exacerbate positive feedbacks between climate and permafrost thawing. We present a diagram that summarizes the social and ecological factors that influence Arctic NDVI. The NDVI should be viewed as a powerful monitoring tool that integrates the cumulative effect of a multitude of factors affecting Arctic land-cover change.

Controls over intra-seasonal dynamics of AVHRR NDVI for the Arctic tundra in northern Alaska

We analysed the Normalized Difference Vegetation Index (NDVI), calculated from biweekly NOAA Advanced Very High Resolution Radiometer (AVHRR) images for northern Alaska at both regional (latitudinal gradients) and site scales. Our objectives were to determine if tundra types and arctic subzones could be differentiated in terms of intra-seasonal patterns of greenness, and to construct the relationships between NDVI and air and soil temperatures. There were common intra-seasonal patterns of NDVI along two latitudinal transects, and a general latitudinal gradient of time of greenness onset and length of growing season was observed. At the site scale, in most cases, wet tundra (WT) had the lowest NDVI values throughout the year, while shrub tundra (ST) had the highest values. The peak NDVI appeared in the period of 22 July to 4 August, with mean values of 0.552 for ST, 0.495 for moist acidic tundra (MAT), 0.434 for sandy tundra (Sandy), 0.426 for moist non-acidic tundra (MNT) and 0.343 for WT. The earliest onset of greenness occurred in ST, followed by MAT, Sandy and MNT, while WT had the latest onset. There were positive linear relationships between bi-weekly NDVI anomalies and air temperature, soil surface temperature, and 20 cm depth soil temperature anomalies in the region. Plant functional type abundances, tundra type, air and soil temperatures all appeared to influence the seasonal dynamics of NDVI.

Spatial characteristics of AVHRR‐NDVI along latitudinal transects in northern Alaska

Abstract Two-weekly AVHRR images were used to examine spatial patterns of the normalized difference vegetation index (NDVI) and their relationships with environmental variables for moist acidic tundra (MAT) and moist non-acidic tundra (MNT) along two latitudinal transects in northern Alaska. The NDVI database was derived from a 5-yr time series (1995–1999) of two-weekly AVHRR composites for Alaska. A digital climate map, digital elevation map and vegetation map were processed and overlain with the NDVI grid. Homogeneous vegetation patches for both MAT and MNT were defined as sample sites using infrared aerial photos, MSS images and the vegetation map along the transects. Linear and non-linear regression modeling were performed between NDVI indices and environmental variables, total summer warmth (TSW) and elevation. It was demonstrated that along both western and eastern transects, there were obvious latitudinal trends of peak NDVI (AP-NDVI), average growing season NDVI (GS-NDVI), and early June NDVI (EJ-NDVI). In most cases, MNT had lower NDVI values than MAT throughout the year. There were significant (p < 0.01) relations between NDVI (AP-NDVI, GS-NDVI and EJ-NDVI) and total summer warmth (TSW) and elevation in the region. EJ-NDVI showed the strongest correlation with TSW or elevation, making it the most sensitive NDVI indicator along environmental gradients in northern Alaska. NDVI was likely controlled by TSW and elevation, with the former being dominant. Nomenclature: Yurtsev (1994). Abbreviations: AK = Alaska; AP-NDVI = Annual peak NDVI; AVHRR = Advanced Very High Resolution Radiometer; DEM = Digital elevation model; EJ-NDVI = Early June NDVI; GS-NDVI = Growing season NDVI; LAI = Leaf-area index; MAT = Moist acidic tundra; MNT = Moist non-acidic tundra; NDVI = Normalized difference vegetation index; TSW = Total summer warmth.

Climate change reduces extent of temperate drylands and intensifies drought in deep soils

Drylands cover 40% of the global terrestrial surface and provide important ecosystem services. While drylands as a whole are expected to increase in extent and aridity in coming decades, temperature and precipitation forecasts vary by latitude and geographic region suggesting different trajectories for tropical, subtropical, and temperate drylands. Uncertainty in the future of tropical and subtropical drylands is well constrained, whereas soil moisture and ecological droughts, which drive vegetation productivity and composition, remain poorly understood in temperate drylands. Here we show that, over the twenty first century, temperate drylands may contract by a third, primarily converting to subtropical drylands, and that deep soil layers could be increasingly dry during the growing season. These changes imply major shifts in vegetation and ecosystem service delivery. Our results illustrate the importance of appropriate drought measures and, as a global study that focuses on temperate drylands, highlight a distinct fate for these highly populated areas.

Detecting urban warming signals in climate records.

Determining whether air temperatures recorded at meteorological stations have been contaminated by the urbanization process is still a controversial issue at the global scale. With support of historical remote sensing data, this study examined the impacts of urban expansion on the trends of air temperature at 69 meteorological stations in Beijing, Tianjin, and Hebei Province over the last three decades. There were significant positive relations between the two factors at all stations. Stronger warming was detected at the meteorological stations that experienced greater urbanization, i.e., those with a higher urbanization rate. While the total urban area affects the absolute temperature values, the change of the urban area (urbanization rate) likely affects the temperature trend. Increases of approximately 10% in urban area around the meteorological stations likely contributed to the 0.13°C rise in air temperature records in addition to regional climate warming. This study also provides a new approach to selecting reference stations based on remotely sensed urban fractions. Generally, the urbanization-induced warming contributed to approximately 44.1% of the overall warming trends in the plain region of study area during the past 30 years, and the regional climate warming was 0.30°C (10 yr)−1 in the last three decades.

Recent Changes in Arctic Vegetation: Satellite Observations and Simulation Model Predictions

This chapter provides an overview of observed changes in vegetation productivity in Arctic tundra and boreal forest ecosystems over the past 3 decades, based on satellite remote sensing and other observational records, and relates these to climate variables and sea ice conditions. The emerging patterns and relationships are often complex but clearly reveal a contrast in the response of the tundra and boreal biomes to recent climate change, with the tundra showing increases and undisturbed boreal forests mostly reductions in productivity. The possible reasons for this divergence are discussed and the consequences of continued climate warming for the vegetation in the Arctic region assessed using ecosystem models, both at the biome-scale and at high spatial resolution focussing on plant functional types in the tundra and the tundra-forest ecotones.

Evaluating Spatial-Temporal Dynamics of Net Primary Productivity of Different Forest Types in Northeastern China Based on Improved FORCCHN

An improved individual-based forest ecosystem carbon budget model for China (FORCCHN) was applied to investigate the spatial-temporal dynamics of net primary productivity of different forest types in northeastern China. In this study, the forests of northeastern China were categorized into four ecological types according to their habitats and generic characteristics (evergreen broadleaf forest, deciduous broadleaf forest, evergreen needleleaf forest and deciduous needleleaf forest). The results showed that distribution and change of forest NPP in northeastern China were related to the different forest types. From 1981 to 2002, among the forest types in northeastern China, per unit area NPP and total NPP of deciduous broadleaf forest were the highest, with the values of 729.4 gC/(m2•yr) and 106.0 TgC/yr, respectively, followed by mixed broadleaf- needleleaf forest, deciduous needleleaf forest and evergreen needleleaf forest. From 1981 to 2002, per unit area NPP and total NPP of different forest types in northeastern China exhibited significant trends of interannual increase, and rapid increase was found between the 1980s and 1990s. The contribution of the different forest type’s NPP to total NPP in northeastern China was clearly different. The greatest was deciduous broadleaf forest, followed by mixed broadleaf- needleleaf forest and deciduous needleleaf forest. The smallest was evergreen needleleaf forest. Spatial difference in NPP between different forest types was remarkable. High NPP values of deciduous needleleaf forest, mixed broadleaf- needleleaf forest and deciduous broadleaf forest were found in the Daxing’anling region, the southeastern of Xiaoxing’anling and Jilin province, and the Changbai Mountain, respectively. However, no regional differences were found for evergreen needleleaf NPP. This study provided not only an estimation NPP of different forest types in northeastern China but also a useful methodology for estimating forest carbon storage at regional and global levels.

Satellite-based estimation of daily average net radiation under clear-sky conditions

Daily average net radiation (DANR) is an important variable for estimating evapotranspiration from satellite data at regional scales, and is used for atmospheric and hydrologic modeling, as well as ecosystem management. A scheme is proposed to estimate the DANR over large heterogeneous areas under clear-sky conditions using only remotely sensed data. The method was designed to overcome the dependence of DANR estimates on ground data, and to map spatially consistent and reasonably distributed DANR, by using various land and atmospheric data products retrieved from MODIS (Moderate Resolution Imaging Spectroradiometer) data. An improved sinusoidal model was used to retrieve the diurnal variations of downward shortwave radiation using a single instantaneous value from satellites. The downward shortwave component of DANR was directly obtained from this instantaneous value, and the upward shortwave component was estimated using satellite-derived albedo products. Four observations of air temperature from MOD07_L2 and MYD07_L2 data products were used to derive the downward longwave component of DANR, while the upward longwave component was estimated using the land surface temperature (LST) and the surface emissivity from MOD11_L2. Compared to in situ observations at the cropland and grassland sites located in Tongyu, northern China, the root mean square error (RMSE) of DANR estimated for both sites under clear-sky conditions was 37 W m−2 and 40 W m−2, respectively. The errors in estimation of DANR were comparable to those from previous satellite-based methods. Our estimates can be used for studying the surface radiation balance and evapotranspiration.