Effects of nitrogen limitation on hydrological processes in CLM4-CN

[1] The role of nitrogen limitation on photosynthesis downregulation and stomatal conductance has a significant influence on evapotranspiration and runoff. In the current Community Land Model with coupled Carbon and Nitrogen cycles (CLM4-CN), however, the carbon and water coupling in stomata is not linked to nitrogen limitation. We modify the incomplete linkages between carbon, nitrogen, and water, and examine how nitrogen limitation affects hydrological processes in CLM4-CN. We then evaluate if the modification can improve the simulation of carbon and water fluxes. Applying the effects of nitrogen limitation on stomatal conductance significantly decreases leaf photosynthesis. It leads to a reduction in canopy transpiration, thereby increasing total runoff, mainly due to increasing subsurface runoff. More available soil water for vegetation from the reduced transpiration helps increase gross primary productivity (GPP) in the relatively moisture-limited regions of grassland/steppe and savanna. However, in the tropics and boreal forest regions, changes in soil water by nitrogen limitation are insignificant, and GPP decreases directly by down-regulated leaf photosynthesis. Decreasing canopy transpiration and increasing runoff from nitrogen limitation improve simulating latent heat flux and runoff by reducing high biases for latent heat flux in the tropics and low biases for runoff in the tropics and northern high latitudes. In addition, the CLM4-CN with leaf-level nitrogen limitation reduces model biases in tropical GPP. Nitrogen limitation on the leaf-level significantly affects hydrological processes in CLM4-CN and improves the simulation of carbon and water fluxes. This process should be included with other recent improvements to reduce model biases as much as possible

Reducing Uncertainties in Applying Remotely Sensed Land Use and Land Cover Maps in Land-Atmosphere Interaction: Identifying Change in Space and Time

Land use and land cover (LULC) data are a central component of most land-atmosphere interaction studies, but there are two common and highly problematic scale mismatches between LULC and climate data. First, in the spatial domain, researchers rarely consider the impact of scaling up fine-scale LULC data to match coarse-scale climate datasets. Second, in the temporal domain, climate data typically have sub-daily, daily, monthly, or annual resolution, but LULC datasets often have much coarser (e.g., decadal) resolution. We first explored the effect of three spatial scaling methods on correlations among LULC data and a land surface climatic variable, latent heat flux in China. Scaling by a fractional method preserved significant correlations among LULC data and latent heat flux at all three studied scales (0.5°, 1.0°, and 2.5°), whereas nearest-neighbor and majority-aggregation methods caused these correlations to diminish and even become statistically non-significant at coarser spatial scales (i.e., 2.5°). In the temporal domain, we identified fractional changes in croplands, forests, and grasslands in China using a recently developed and annually resolved time series of LULC maps from 1982 to 2012. Relative to common LULC change (LULCC) analyses conducted over two-time steps or several time periods, this annually resolved, 31-year time series of LULC maps enables robust interpretation of LULCC. Specifically, the annual resolution of these data enabled us to more precisely observe three key and statistically significant LULCC trends and transitions that could have consequential effects on land-atmosphere interaction: (1) decreasing grasslands to increasing croplands in the Northeast China plain and the Yellow river basin, (2) decreasing croplands to increasing forests in the Yangtze river basin, and (3) decreasing grasslands to increasing forests in Southwest China. Our study not only demonstrates the importance of using a fractional spatial rescaling method, but also illustrates the value of annually resolved LULC time series for detecting significant trends and transitions in LULCC, thus potentially facilitating a more robust use of remotely sensed data in land-atmosphere interaction studies

Effects of Temperature on Development and Voltinism of Chaetodactylus krombeini (Acari: Chaetodactylidae): Implications for Climate Change Impacts

Temperature plays an important role in the growth and development of arthropods, and thus the current trend of climate change will alter their biology and species distribution. We used Chaetodactylus krombeini (Acari: Chaetodactylidae), a cleptoparasitic mite associated with Osmia bees (Hymenoptera: Megachilidae), as a model organism to investigate how temperature affects the development and voltinism of C. krombeini in the eastern United States. The effects of temperature on the stage-specific development of C. krombeini were determined at seven constant temperatures (16.1, 20.2, 24.1, 27.5, 30.0, 32.4 and 37.8°C). Parameters for stage-specific development, such as threshold temperatures and thermal constant, were determined by using empirical models. Results of this study showed that C. krombeini eggs developed successfully to adult at all temperatures tested except 37.8°C. The nonlinear and linear empirical models were applied to describe quantitatively the relationship between temperature and development of each C. krombeini stage. The nonlinear Lactin model estimated optimal temperatures as 31.4, 32.9, 32.6 and 32.5°C for egg, larva, nymph, and egg to adult, respectively. In the linear model, the lower threshold temperatures were estimated to be 9.9, 14.7, 13.0 and 12.4°C for egg, larva, nymph, and egg to adult, respectively. The thermal constant for each stage completion were 61.5, 28.1, 64.8 and 171.1 degree days for egg, larva, nymph, and egg to adult, respectively. Under the future climate scenarios, the number of generations (i.e., voltinism) would increase more likely by 1.5 to 2.0 times by the year of 2100 according to simulation. The findings herein firstly provided comprehensive data on thermal development of C. krombeini and implications for the management of C. krombeini populations under global warming were discussed

April Vegetation Dynamics and Forest–Climate Interactions in Central Appalachia

The study of land–atmosphere (L–A) interactions is an emerging field in which the effects of the land on the atmosphere are strongly considered. Though this coupled approach is becoming more popular in atmospheric research, L–A interactions are not fully understood, especially in temperate regions. This study provides the first in-depth investigation of L–A interactions and their impacts on near-surface climate conditions in the Appalachian region of the Eastern United States. By way of statistical analysis, we explore vegetation dynamics, L–A interactions, and the consequences for near-surface climate, along with the competing effects of the albedo (energy) and moisture (evapotranspiration and soil moisture) feedback. Based on the results from linear regression, composite, and correlation analyses, we conclude that: (1) a statistically significant increasing trend in April vegetation exists from 1982 to 2015 in central Appalachia; (2) there was empirical evidence that this increasing vegetation trend was significant and altered near-surface climatic conditions, as indicated by significantly enhanced latent heat flux, 2 m-specific humidity, and soil moisture; and (3) the dominant biogeophysical process responsible for the changes in near-surface climate conditions could be the positive moisture feedback process

Validation and Comparison of Climate Reanalysis Data in the East Asian Monsoon Region

Understanding East Asian monsoon (EAM) has been a crucial issue due to its socio-economic effects on one-fifth of the world’s population and its interactions with the global climate system. However, the reliabilities of climate reanalysis data are still uncertain at varying temporal and spatial scales. In this study, we examined the correlations and differences for climate reanalyses with weather observations and suggested the best climate reanalysis for the EAM region. The three reanalyses of ERA5, JRA55, and NCEP2 along with a gridded observation (CRU) were evaluated using the correlation coefficients (Pearson, Spearman, and Kendall), difference statistics (RMSE and bias), and Taylor diagrams, comparing their annual and seasonal temperatures and precipitations with those from the total of 537 weather stations across China, North Korea, South Korea, and Japan. We found that ERA5 showed the best performance in reproducing temporal variations in temperature with the highest correlations in annual, summer, and autumn, and the smallest RMSEs and biases for all seasons and annually. For precipitation, among the three reanalysis datasets, ERA5 had the highest correlations, annually and in four seasons, with the smallest RMSEs, annually and in spring, summer and autumn, and the smallest biases, annually and in summer and autumn. Regarding spatial variations, ERA5 was also the most suitable reanalysis data in representing the annual and seasonal climatological averages

Land Cover and Land Use Mapping of the East Asian Summer Monsoon Region from 1982 to 2015

Owing to the recent intensification of the East Asian summer monsoon, the frequency of floods and dry spells, which commonly affect more than one billion people, is continuously increasing. Thus, understanding the causes of changes in the EASM is paramount. Land cover and land use change can perturb a regional climate system through biogeophysical and biogeochemical processes. However, due to the scarcity of temporally continuous land cover and land use maps, the impact of land cover and land use change on the EASM is still not thoroughly explored. In the present study, this limitation was addressed via the production of annual land cover and land use maps of the East Asian summer monsoon region covering a period of 34 years (1982–2015). This was achieved through a random forest classification of phenological information derived from the Advanced Very High-Resolution Radiometer Global Inventory Modeling and Mapping Studies Normalized Difference Vegetation Index dataset and terrain information from the Advanced Land Observing Satellite World 3D—30 m Digital Surface Model data. Nine ecological zones were involved in the random forest classification and the classified map in 2015 was validated using very high-resolution images obtained from Google Earth. The overall accuracy (73%) of the classification map surpasses the Moderate Resolution Imaging Spectroradiometer and Global Land Surface Satellite land cover products for the same year by ~7% and 4%, respectively. According to our classified maps, croplands and forests significantly increased in the East Asian summer monsoon region from 1982 to 2015. The dominant transition in these three decades was from croplands to forests

Seasonal tropospheric cooling in Northeast China associated with cropland expansion

Large-scale agricultural expansion can influence near-surface climate by altering surface energy fluxes, water, and albedo. It is less clear whether such effects extend through the full troposphere and how such effects vary in time. Here we use a novel dataset documenting the massive land use and land cover change due to agricultural expansion in Northeast China from 1982 to 2010 to assess how such expansion has influenced climate over the full troposphere. Confronting our land classification and climate data with a number of statistical approaches (linear regression, correlation analysis, Granger-causality), we find that cropland significantly increased by ∼28% over the near 30 year period in Northeast China-an average rate of nearly a percentage per year. This massive 30 year agricultural expansion is tightly associated with near-surface cooling identified in station data during the late growing season (August to September). Assuming no cropland expansion over the 30 year period, surface temperature would have increased by 0.93 °C ± 0.4 °C. Furthermore, the fingerprint of cropland-associated cooling extends upward into the atmospheric column, influencing the vertical structure of the regional troposphere and potentially its circulation. For every 10 percentage points increase in cropland fraction over Northeast China, regional full-troposphere temperature and geopotential height significantly decrease by 0.2 °C–0.6 °C and 20 m–80 m, respectively. These observed relationships are remarkably coherent across datasets, methodological choices, atmospheric levels, and theory, suggesting that the observational effects we identify are robust and imply the possibility of detectable land use change effects on regional circulation, with potential consequences for the East Asian monsoon

Effects of nitrogen limitation on hydrological processes in CLM4‐CN

[1] The role of nitrogen limitation on photosynthesis downregulation and stomatal conductance has a significant influence on evapotranspiration and runoff. In the current Community Land Model with coupled Carbon and Nitrogen cycles (CLM4‐CN), however, the carbon and water coupling in stomata is not linked to nitrogen limitation. We modify the incomplete linkages between carbon, nitrogen, and water, and examine how nitrogen limitation affects hydrological processes in CLM4‐CN. We then evaluate if the modification can improve the simulation of carbon and water fluxes. Applying the effects of nitrogen limitation on stomatal conductance significantly decreases leaf photosynthesis. It leads to a reduction in canopy transpiration, thereby increasing total runoff, mainly due to increasing subsurface runoff. More available soil water for vegetation from the reduced transpiration helps increase gross primary productivity (GPP) in the relatively moisture‐limited regions of grassland/steppe and savanna. However, in the tropics and boreal forest regions, changes in soil water by nitrogen limitation are insignificant, and GPP decreases directly by down‐regulated leaf photosynthesis. Decreasing canopy transpiration and increasing runoff from nitrogen limitation improve simulating latent heat flux and runoff by reducing high biases for latent heat flux in the tropics and low biases for runoff in the tropics and northern high latitudes. In addition, the CLM4‐CN with leaf‐level nitrogen limitation reduces model biases in tropical GPP. Nitrogen limitation on the leaf‐level significantly affects hydrological processes in CLM4‐CN and improves the simulation of carbon and water fluxes. This process should be included with other recent improvements to reduce model biases as much as possible

AGU hydrology days 2007

2007 annual AGU hydrology days was held at Colorado State University on March 19 - March 21, 2007.Includes bibliographical references.Effects of land cover change over the Indian subcontinent during the preceding March through May (MAM) on early Indian summer monsoon (ISM) rainfall were examined using the Normalized Difference Vegetation Index (NDVI) and Global Precipitation Climatology Project precipitation for the period of 1982~2003. MAM NDVI anomalies have increased significantly in western and northern India. NDVI anomalies are correlated with the decreasing trend of early ISM rainfall. Decreasing rainfall originates from the decreased land-sea thermal contrast, which is due to the decreasing trend of July sensible heat flux in central and northern India. This is related to the increase in the preceding MAM NDVI anomalies because early ISM rainfall is significantly and negatively correlated with the standardized principal component of the first leading empirical orthogonal function for the preceding MAM NDVI anomalies. Also, composite differences of early ISM rainfall for the five years of highest and of lowest MAM NDVI anomalies demonstrate that early ISM rainfall is significantly less for the years of highest MAM NDVI anomalies. Composite differences of wind vectors and divergence in the upper level also support the conclusion that the weak early Indian summer monsoonal circulation is due to the increase in land cover during the preceding spring, which would promote an increase in latent heat flux and a decrease in sensible heat flux thereby favoring a reduced horizontal temperature gradient

Potential feedback of recent vegetation changes on summer rainfall in the Sahel

<p>The Sahel region of Northern Africa is home to more than 50 million people for whom summer rainfall is a crucial water resource in terms of food security and societal stability. Using satellite-based Normalized Difference Vegetation Index (NDVI) and gridded observational precipitation records during 1982–2012, we detected a significant increase (<i>p</i>-value < 0.01) in both vegetation greenness and monsoon rainfall over the Sahel since the early 1980s. A significant positive association between NDVI and precipitation was observed for most of the Sahel during the boreal summer. In further efforts to examine the potential causal association behind the positive correlation, we found that summer vegetation greenness Granger-causes summer rainfall in the Sahel. Regarding the physical process behind this identified Granger causality, we inferred that significantly increasing latent heat flux and specific humidity resulted in increasing summer rainfall during the years of high NDVI in the Sahel. A significant increase in the percentage of land used for crops and pastures was a potential cause of the recent vegetation change. Our findings indicated that the positive effect of vegetation cover through agricultural activities on regional precipitation could lead to a positive feedback between the vegetation and climate in the water-limited Sahel region.</p