ALBERT

Description: Despite the importance of mangrove ecosystems in the global carbon budget, the relationships between environmental drivers and carbon dynamics in these forests remain poorly understood. This limited understanding is partly a result of the challenges associated with in situ flux studies. Tower-based carbon dioxide eddy covariance (EC) systems are installed in only a few mangrove forests worldwide and the longest EC record from the Florida Everglades contains less than 9 yr of observations. A primary goal of the present study was to develop a methodology to estimate canopy-scale photosynthetic light use efficiency in this forest. These tower-based observations represent a basis for associating CO2 fluxes with canopy light use properties, and thus provide the means for utilizing satellite-based reflectance data for larger-scale investigations. We present a model for mangrove canopy light use efficiency utilizing the enhanced green vegetation index (EVI) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) that is capable of predicting changes in mangrove forest CO2 fluxes caused by a hurricane disturbance and changes in regional environmental conditions, including temperature and salinity. Model parameters are solved for in a Bayesian framework. The model structure requires estimates of ecosystem respiration (RE) and we present the first-ever tower-based estimates of mangrove forest RE derived from night-time CO2 fluxes. Our investigation is also the first to show the effects of salinity on mangrove forest CO2 uptake, which declines 5% per each 10 parts per thousand (ppt) increases in salinity. Light use efficiency in this forest declines with increasing daily photosynthetic active radiation, which is an important departure from the assumption of constant light use efficiency typically applied in satellite-driven models. The model developed here provides a framework for estimating CO2 uptake by these forests from reflectance data and information about environmental conditions.

Description: Flood estimation and flood management have traditionally been the domain of hydrologists, water resources engineers and statisticians, and disciplinary approaches have abound. Dominant views have been shaped; one example is the catchment perspective: floods are formed and influenced by the interaction of local, catchment-specific characteristics, such as meteorology, topography and geology. These traditional views have been beneficial, but they have a narrow framing. In this paper we contrast traditional views with broader perspectives that are emerging from an improved understanding of the climatic context of floods. We conclude: (1) extending the traditional system boundaries (local catchment, recent decades, hydrological/hydraulic processes) opens up exciting possibilities for better understanding and improved tools for flood risk assessment and management. (2) Statistical approaches in flood estimation need to be complemented by the search for the causal mechanisms and dominant processes in the atmosphere, catchment and river system that leave their fingerprints on flood characteristic. (3) Natural climate variability leads to time-varying flood characteristics, and this variation may be partially quantifiable and predictable, with the perspective of a dynamic, climate informed flood risk management. (4) Efforts are needed to fully account for factors that contribute to changes in all three risk components (hazard, exposure, vulnerability), and to better understand the interactions between society and floods. (5) Given the global scale and societal importance, we call for the organization of an international multidisciplinary collaboration and data sharing initiative to understand further the links between climate and flooding and to advance flood research.

Description: Flood estimation and flood management have traditionally been the domain of hydrologists, water resources engineers and statisticians, and disciplinary approaches abound. Dominant views have been shaped; one example is the catchment perspective: floods are formed and influenced by the interaction of local, catchment-specific characteristics, such as meteorology, topography and geology. These traditional views have been beneficial, but they have a narrow framing. In this paper we contrast traditional views with broader perspectives that are emerging from an improved understanding of the climatic context of floods. We come to the following conclusions: (1) extending the traditional system boundaries (local catchment, recent decades, hydrological/hydraulic processes) opens up exciting possibilities for better understanding and improved tools for flood risk assessment and management. (2) Statistical approaches in flood estimation need to be complemented by the search for the causal mechanisms and dominant processes in the atmosphere, catchment and river system that leave their fingerprints on flood characteristics. (3) Natural climate variability leads to time-varying flood characteristics, and this variation may be partially quantifiable and predictable, with the perspective of dynamic, climate-informed flood risk management. (4) Efforts are needed to fully account for factors that contribute to changes in all three risk components (hazard, exposure, vulnerability) and to better understand the interactions between society and floods. (5) Given the global scale and societal importance, we call for the organization of an international multidisciplinary collaboration and data-sharing initiative to further understand the links between climate and flooding and to advance flood research.

Description: This study presents a novel bias correction scheme for Regional Climate Model (RCM) precipitation ensembles. A primary advantage of using model ensembles for climate change impact studies is that the uncertainties associated with the systematic error can be quantified through the ensemble spread. Currently, however, most of the conventional bias correction methods adjust all the ensemble members to one reference observation. As a result, the ensemble spread is degraded during bias correction. Since the observation is only one case of many possible realizations due to the climate natural variability, bias correction scheme should preserve ensemble spread within the bounds of natural variability (i.e. sampling uncertainty). To demonstrate the proposed methodology, an application to the Thorverton catchment in the southwest of England is presented. For the ensemble, 11-members from the Hadley Centre Regional Climate Model (HadRM3-PPE) Data are used and monthly bias correction has been done for the baseline time period from 1961 to 1990. In the typical conventional method, monthly mean precipitation of each of the ensemble members are nearly identical to the observation, i.e. the ensemble spread is removed. In contrast, the proposed method corrects the biases while maintain ensemble spread within the natural variability of observations.

Description: Considering the feedback loops in radiation, temperature, and soil moisture with alterations in rainfall patterns, the influence of the changing monsoon on net ecosystem CO2 exchange can be critical to the estimation of carbon balance in Asia. In this paper, we examined the eddy covariance CO2 fluxes observed from 2004 to 2008 in two major plant functional types in KoFlux, i.e., the Gwangneung deciduous forest (GDK) site and the Haenam farmland (HFK) site. The objectives of the study were to (1) quantify the net ecosystem CO2 exchange (NEE), ecosystem respiration (RE), and gross primary production (GPP), (2) examine their interannual patterns, and (3) assess the mechanism for the coupling of carbon and water exchange associated with the summer monsoon. The GDK site, which had a maximum leaf area index (LAI) of ~5, was on average a relatively weak carbon sink with NEE of −84 gC m−2 y−1, RE of 1028 gC m−2 y−1, and GPP of 1113 gC m−2 y−1. Despite about 20% larger GPP (of 1321 gC m−2 y−1) in comparison with the GDK site, the HFK site (with the maximum LAI of 3 to 4) was a weaker carbon sink with NEE of −58 gC m−2 y−1 because of greater RE of 1263 gC m−2 y−1. In both sites, the annual patterns of NEE and GPP had a striking "mid-season depression" each year with two distinctive peaks of different timing and magnitude, whereas RE did not. The mid-season depression at the GDK site occurred typically from early June to late August, coinciding with the season of summer monsoon when the solar radiation decreased substantially due to frequent rainfalls and cloudiness. At the HFK site, the mid-season depression began earlier in May and continued until the end of July due to land use management (e.g., crop rotation) in addition to such disturbances as summer monsoon and typhoons. Other flux observation sites in East Asia also show a decline in radiation but with a lesser degree during the monsoon season, resulting in less pronounced depression in NEE. In our study, however, the observed depression in NEE changed the forest and farmland from a carbon sink to a source in the middle of the growing season. Consequently, the annually integrated values of NEE lies on the low end of the range reported in the literature. Such a delicate coupling between carbon and water cycles may turn these ecosystems into a stronger carbon sink with the projected trends of less frequent but more intensive rainfalls in this region.

Description: We used a 3-D regional atmospheric chemistry transport model (WRF-Chem) to examine processes that determine O3 in East Asia; in particular, we focused on O3 dry deposition, which is an uncertain research area due to insufficient observation and numerical studies in East Asia. Here, we compare two widely used dry deposition parameterization schemes, Wesely and M3DRY, which are used in the WRF-Chem and CMAQ models, respectively. The O3 dry deposition velocities simulated using the two aforementioned schemes under identical meteorological conditions show considerable differences (a factor of 2) due to surface resistance parameterization discrepancies. The O3 concentration differed by up to 10 ppbv for the monthly mean. The simulated and observed dry deposition velocities were compared, which showed that the Wesely scheme model is consistent with the observations and successfully reproduces the observed diurnal variation. We conduct several sensitivity simulations by changing the land use data, the surface resistance of the water and the model's spatial resolution to examine the factors that affect O3 concentrations in East Asia. As shown, the model was considerably sensitive to the input parameters, which indicates a high uncertainty for such O3 dry deposition simulations. Observations are necessary to constrain the dry deposition parameterization and input data to improve the East Asia air quality models.

Description: Despite the importance of mangrove ecosystems in the global carbon budget, the relationships between environmental drivers and carbon dynamics in these forests remain poorly understood. This limited understanding is partly a result of the challenges associated with in situ flux studies. Tower-based CO2 eddy covariance (EC) systems are installed in only a few mangrove forests worldwide, and the longest EC record from the Florida Everglades contains less than 9 years of observations. A primary goal of the present study was to develop a methodology to estimate canopy-scale photosynthetic light use efficiency in this forest. These tower-based observations represent a basis for associating CO2 fluxes with canopy light use properties, and thus provide the means for utilizing satellite-based reflectance data for larger scale investigations. We present a model for mangrove canopy light use efficiency utilizing the enhanced green vegetation index (EVI) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) that is capable of predicting changes in mangrove forest CO2 fluxes caused by a hurricane disturbance and changes in regional environmental conditions, including temperature and salinity. Model parameters are solved for in a Bayesian framework. The model structure requires estimates of ecosystem respiration (RE), and we present the first ever tower-based estimates of mangrove forest RE derived from nighttime CO2 fluxes. Our investigation is also the first to show the effects of salinity on mangrove forest CO2 uptake, which declines 5% per each 10 parts per thousand (ppt) increase in salinity. Light use efficiency in this forest declines with increasing daily photosynthetic active radiation, which is an important departure from the assumption of constant light use efficiency typically applied in satellite-driven models. The model developed here provides a framework for estimating CO2 uptake by these forests from reflectance data and information about environmental conditions.

Description: The Korea Institute of Atmospheric Prediction Systems (KIAPS) has been developing a new global numerical weather prediction model and an advanced data assimilation system. As part of the KIAPS package for observation processing (KPOP) system for data assimilation, preprocessing, and quality control modules for bending-angle measurements of global positioning system radio occultation (GPS-RO) data have been implemented and examined. The GPS-RO data processing system is composed of several steps for checking observation locations, missing values, physical values for Earth radius of curvature, and geoid undulation. An observation-minus-background check is implemented by use of a one-dimensional observational bending-angle operator, and tangent point drift is also considered in the quality control process. We have tested GPS-RO observations utilized by the Korean Meteorological Administration (KMA) within KPOP, based on both the KMA global model and the National Center for Atmospheric Research Community Atmosphere Model with Spectral Element dynamical core (CAM-SE) as a model background. Background fields from the CAM-SE model are incorporated for the preparation of assimilation experiments with the KIAPS local ensemble transform Kalman filter (LETKF) data assimilation system, which has been successfully implemented to a cubed-sphere model with unstructured quadrilateral meshes. As a result of data processing, the bending-angle departure statistics between observation and background show significant improvement. Also, the first experiment in assimilating GPS-RO bending angle from KPOP within KIAPS-LETKF shows encouraging results.

Description: We use a 3-D regional atmospheric chemistry transport model (WRF-Chem) to examine ozone dry deposition in East Asia, which is an important but uncertain research area because of insufficient observation and numerical studies focusing on East Asia. Here we compare two widely used dry deposition parameterization schemes, the Wesely and M3DRY schemes, which are used in the WRF-Chem and Community Multiscale Air Quality (CMAQ) models, respectively. Simulated ozone dry deposition velocities with the two schemes under identical meteorological conditions show considerable differences (a factor of 2) owing to surface resistance parameterization discrepancies. Resulting ozone concentrations differ by up to 10 ppbv for a monthly mean in May when the peak ozone typically occurs in East Asia. An evaluation of the simulated dry deposition velocities shows that the Wesely scheme calculates values with more pronounced diurnal variation than the M3DRY and results in a good agreement with the observations. However, we find significant changes in simulated ozone concentrations using the Wesely scheme but with different surface type data sets, indicating the high sensitivity of ozone deposition calculations to the input data. The need is high for observations to constrain the dry deposition parameterization and its input data to improve the use of air quality models for East Asia.

Description: The Korea Institute of Atmospheric Prediction Systems (KIAPS) has been developing a new global numerical weather prediction model and an advanced data assimilation system. As part of the KIAPS Package for Observation Processing (KPOP) system for data assimilation, preprocessing and quality control modules for bending angle measurements of global positioning system radio occultation (GPS-RO) data have been implemented and examined. GPS-RO data processing system is composed of several steps for checking observation locations, missing values, physical values for Earth radius of curvature, and geoid undulation. An observation-minus-background check is implemented by use of a one-dimensional observational bending angle operator and tangent point drift is also considered in the quality control process. We have tested GPS-RO observations utilized by the Korean Meteorological Administration (KMA) within KPOP, based on both the KMA global model and the National Center for Atmospheric Research (NCAR) Community Atmosphere Model-Spectral Element (CAM-SE) as a model background. Background fields from the CAM-SE model are incorporated for the preparation of assimilation experiments with the KIAPS-LETKF data assimilation system, which has been successfully implemented to a cubed-sphere model with fully unstructured quadrilateral meshes. As a result of data processing, the bending angle departure statistics between observation and background shows significant improvement. Also, the first experiment in assimilating GPS-RO bending angle resulting from KPOP within KIAPS-LETKF shows encouraging results.