Differences In Model Parameterization Research Articles

Estimating global cropland production from 1961 to 2010

Abstract. Global cropland net primary production (NPP) has tripled over the last 50 years, contributing 17–45 % to the increase in global atmospheric CO2 seasonal amplitude. Although many regional-scale comparisons have been made between statistical data and modeling results, long-term national comparisons across global croplands are scarce due to the lack of detailed spatiotemporal management data. Here, we conducted a simulation study of global cropland NPP from 1961 to 2010 using a process-based model called Vegetation–Global Atmosphere–Soil (VEGAS) and compared the results with Food and Agriculture Organization of the United Nations (FAO) statistical data on both continental and country scales. According to the FAO data, the global cropland NPP was 1.3, 1.8, 2.2, 2.6, 3.0, and 3.6 PgC yr−1 in the 1960s, 1970s, 1980s, 1990s, 2000s, and 2010s, respectively. The VEGAS model captured these major trends on global and continental scales. The NPP increased most notably in the US Midwest, western Europe, and the North China Plain and increased modestly in Africa and Oceania. However, significant biases remained in some regions such as Africa and Oceania, especially in temporal evolution. This finding is not surprising as VEGAS is the first global carbon cycle model with full parameterization representing the Green Revolution. To improve model performance for different major regions, we modified the default values of management intensity associated with the agricultural Green Revolution differences across various regions to better match the FAO statistical data at the continental level and for selected countries. Across all the selected countries, the updated results reduced the RMSE from 19.0 to 10.5 TgC yr−1 (∼ 45 % decrease). The results suggest that these regional differences in model parameterization are due to differences in socioeconomic development. To better explain the past changes and predict the future trends, it is important to calibrate key parameters on regional scales and develop data sets for land management history.

Modelling soil moisture under different land covers in a sub-humid environment of Western Ghats, India

The objective of this study is to apply and test a simple parametric water balance model for prediction of soil moisture regime in the presence of vegetation. The intention was to evaluate the differences in model parameterization and performance when applied to small watersheds under three different types of land covers (Acacia, degraded forest and natural forest). The watersheds selected for this purpose are located in the sub-humid climate within the Western Ghats, Karnataka, India. Model calibration and validation were performed using a dataset comprising depth-averaged soil moisture content measurements made at weekly time steps from October 2004 to December 2008. In addition to this, a sensitivity analysis was carried out with respect to the water-holding capacity of the soils with the aim of explaining the suitability and adaptation of exotic vegetation types under the prevailing climatic conditions. Results indicated reasonably good performance of the model in simulating the pattern and magnitude of weekly average soil moisture content in 150 cm deep soil layer under all three land covers. This study demonstrates that a simple, robust and parametrically parsimonious model is capable of simulating the temporal dynamics of soil moisture content under distinctly different land covers. Also, results of sensitivity analysis revealed that exotic plant species such as Acacia have adapted themselves effectively to the local climate.

GLACE: The Global Land–Atmosphere Coupling Experiment. Part II: Analysis

Abstract The 12 weather and climate models participating in the Global Land–Atmosphere Coupling Experiment (GLACE) show both a wide variation in the strength of land–atmosphere coupling and some intriguing commonalities. In this paper, the causes of variations in coupling strength—both the geographic variations within a given model and the model-to-model differences—are addressed. The ability of soil moisture to affect precipitation is examined in two stages, namely, the ability of the soil moisture to affect evaporation, and the ability of evaporation to affect precipitation. Most of the differences between the models and within a given model are found to be associated with the first stage—an evaporation rate that varies strongly and consistently with soil moisture tends to lead to a higher coupling strength. The first-stage differences reflect identifiable differences in model parameterization and model climate. Intermodel differences in the evaporation–precipitation connection, however, also play a key role.

A Comparison of Synthetic Seismograms for 2D Structures: Semianalytical versus Numerical

Teleseismic wave fields occasionally exhibit rapid changes in travel times and waveforms over distances less than several great-circle degrees when observed at broadband arrays. These rapid changes in wave field suggest the existence of significant structural transitions occurring over scales of several hundred kilometers or less in the mid- and deep mantle. Although approximate analytical methods based on raytracing can be readily adapted to structures having arbitrarily small scale lengths, it is important to validate their accuracy against the predictions of numerical methods. Here we compare synthetics from an approximate ray-based method WKBJ modified (WKM) against the pseudospectral method for a 2D model of the S-velocity anomaly associated with the South African plume. This model consists of a uniform 3% decrease in S velocity over a broad (>10°) region of the mid- and deep mantle beneath South Africa, contiguous at its bottom with a thin (100- to 200-km-thick) zone of low velocity extending 30° westward toward South America along the core-mantle boundary. Transitions between anomalous and radially symmetric structures of the test model are sharp, occurring over l0 km or less. SV and SH wave fields synthesized by the WKM and pseudospectral methods in this model generally agree with each other well. Slight mismatches in the two methods can be understood as the result of either differences in model parameterization or the effects of asymptotic approximations in the ray-based WKM method.

Mid-Holocene and Last Glacial Maximum African monsoon changes as simulated within the Paleoclimate Modelling Intercomparison Project

As part of the Paleoclimate Modelling Intercomparison Project (PMIP), several atmospheric general circulation models have performed climate simulations of the mid-Holocene (6 ka BP) and of the Last Glacial Maximum (LGM) climates (21 ka BP) using the same experimental design for boundary conditions, insolation and CO 2 forcing. PMIP results are used in this study to investigate how the position of the intertropical convergence zone (ITCZ) changes over West Africa throughout the seasonal cycle in these two climates. The Mid-Holocene corresponds to a period of enhanced seasonal cycle with colder winters and warmer summers, leading to an increase of the African monsoon. During LGM, the presence of large ice sheets and lower CO 2 give rise to a colder climate and a reduced summer monsoon. For the two time periods and all the models, it is found that over West Africa, both the atmospheric low level temperature gradient and the position of the maximum of surface temperature control the position of the ITCZ. The energetic changes associated with the change in the hydrological cycle are driven by latent heat release in the atmosphere within the rainbelt and by radiative fluxes north of the ITCZ. The sensible heat flux plays also a non-negligible role over the desert during mid-Holocene. Differences between the PMIP simulations reflect differences in model parameterization, including surface processes and clouds. However, for a given model, the partitioning between the changes in the different heat fluxes is quite similar for the mid-Holocene and the LGM climate change.