A diagnostic study of temperature controls on global terrestrial carbon exchange

The observed interannual variability of atmospheric CO2 reflects short-term variability in sources and sinks of CO2 . Analyses using 13CO2 and O2 suggest that much of the observed interannual variability is due to changes in terrestrial CO2 exchange. First principles, empirical correlations and process models suggest a link between climate variation and net ecosystem exchange, but the scaling of ecological process studies to the globe is notoriously difficult. We sought to identify a component of global CO2 exchange that varied coherently with land temperature anomalies using an inverse modeling approach. We developed a family of simplified spatially aggregated ecosystem models (designated K-model versions) consisting of five compartments: atmospheric CO2 , live vegetation, litter, and two soil pools that differ in turnover times. The pools represent cumulative differences from mean C storage due to temperature variability and can thus have positive or negative values. Uptake and respiration of CO2 are assumed to be linearly dependent on temperature. One model version includes a simple representation of the nitrogen cycle in which changes in the litter and soil carbon pools result in stoichiometric release of plant-available nitrogen, the other omits the nitrogen feedback. The model parameters were estimated by inversion of the model against global temperature and CO2 anomaly data using the variational method. We found that the temperature sensitivity of carbon uptake (NPP) was less than that of respiration in all model versions. Analyses of model and data also showed that temperature anomalies trigger ecosystem changes on multiple, lagged time-scales. Other recent studies have suggested a more active land biosphere at Northern latitudes in response to warming and longer growing seasons. Our results indicate that warming should increase NPP, consistent with this theory, but that respiration should increase more than NPP, leading to decreased or negative NEP. A warming trend could, therefore increase NEP if the indirect feedbacks through nutrients were larger than the direct effects of temperature on NPP and respiration, a conjecture which can be tested experimentally. The fraction of the growth rate not predicted by the K-model represents model and data errors, and variability in anthropogenic release, ocean uptake, and other processes not explicitly represented in the model. These large positive and negative residuals from the K-model may be associated with the Southern Oscillation Index

A meteo-hydrological modelling system for the reconstruction of river runoff: the case of the Ofanto river catchment

Abstract. A meteo-hydrological modelling system has been designed for the reconstruction of long time series of rainfall and river runoff events. The modelling chain consists of the mesoscale meteorological model of the Weather Research and Forecasting (WRF), the land surface model NOAH-MP and the hydrology–hydraulics model WRF-Hydro. Two 3-month periods are reconstructed for winter 2011 and autumn 2013, containing heavy rainfall and river flooding events. Several sensitivity tests were performed along with an assessment of which tunable parameters, numerical choices and forcing data most impacted on the modelling performance.The calibration of the experiments highlighted that the infiltration and aquifer coefficients should be considered as seasonally dependent.The WRF precipitation was validated by a comparison with rain gauges in the Ofanto basin. The WRF model was demonstrated to be sensitive to the initialization time and a spin-up of about 1.5 days was needed before the start of the major rainfall events in order to improve the accuracy of the reconstruction. However, this was not sufficient and an optimal interpolation method was developed to correct the precipitation simulation. It is based on an objective analysis (OA) and a least square (LS) melding scheme, collectively named OA+LS. We demonstrated that the OA+LS method is a powerful tool to reduce the precipitation uncertainties and produce a lower error precipitation reconstruction that itself generates a better river discharge time series. The validation of the river streamflow showed promising statistical indices.The final set-up of our meteo-hydrological modelling system was able to realistically reconstruct the local rainfall and the Ofanto hydrograph

A meteo-hydrological modelling system for the reconstruction of river runoff: the case of the Ofanto river catchment

A meteo-hydrological modelling system has been designed for the reconstruction of long time series of rainfall and river runoff events. The modelling chain consists of the mesoscale meteorological model of the Weather Research and Forecasting (WRF), the land surface model NOAH-MP and the hydrology-hydraulics model WRF-Hydro. Two 3-month periods are reconstructed for winter 2011 and autumn 2013, containing heavy rainfall and river flooding events. Several sensitivity tests were performed along with an assessment of which tunable parameters, numerical choices and forcing data most impacted on the modelling performance. The calibration of the experiments highlighted that the infiltration and aquifer coefficients should be considered as seasonally dependent. The WRF precipitation was validated by a comparison with rain gauges in the Ofanto basin. The WRF model was demonstrated to be sensitive to the initialization time and a spin-up of about 1.5 days was needed before the start of the major rainfall events in order to improve the accuracy of the reconstruction. However, this was not sufficient and an optimal interpolation method was developed to correct the precipitation simulation. It is based on an objective analysis (OA) and a least square (LS) melding scheme, collectively named OA+LS. We demonstrated that the OA+LS method is a powerful tool to reduce the precipitation uncertainties and produce a lower error precipitation reconstruction that itself generates a better river discharge time series. The validation of the river streamflow showed promising statistical indices. The final set-up of our meteo-hydrological modelling system was able to realistically reconstruct the local rainfall and the Ofanto hydrograph

Observing System Simulation Experiments in the Marmara Sea

Poster presented in Symposium for the legacy of Anna Trevisan in Bologna in Oct 201

Satellite-Based Model Parameterization of Diabatic Heating

Future meteorological satellites are expected to provide much needed fine-scale information that can improve the accuracy of weather and climate models. As one application of this improved capability, we introduce the concept of a generalized parameterization framework using satellite datasets that will increase the accuracy and the computational efficiency of weather and climate modeling. In an atmospheric model, several different parameterizations usually are used to reproduce the various physical processes. However, it is generally unrealistic to separate the processes in this artificial way since the observations and physics make no such artificial separation. Thus, we propose a new unified parameterization framework to remove the unrealistic separation between parameterizations

NOAA'S Hurricane Intensity Forecasting Experiment: A Progress Report

An update of the progress achieved as part of the NOAA Intensity Forecasting Experiment (IFEX) is provided. Included is a brief summary of the noteworthy aircraft missions flown in the years since 2005, the first year IFEX flights occurred, as well as a description of the research and development activities that directly address the three primary IFEX goals: 1) collect observations that span the tropical cyclone (TC) life cycle in a variety of environments for model initialization and evaluation; 2) develop and refine measurement strategies and technologies that provide improved real-time monitoring of TC intensity, structure, and environment; and 3) improve the understanding of physical processes important in intensity change for a TC at all stages of its life cycle. Such activities include the real-time analysis and transmission of Doppler radar measurements; numerical model and data assimilation advancements; characterization of tropical cyclone composite structure across multiple scales, from vortex scale to turbulence scale; improvements in statistical prediction of rapid intensification; and studies specifically targeting tropical cyclogenesis, extratropical transition, and the impact of environmental humidity on TC structure and evolution. While progress in TC intensity forecasting remains challenging, the activities described here provide some hope for improvement