Global Land Surface Climate Analysis Based on the Calculation of a Modified Bowen Ratio

A modified Bowen ratio(BRm),the sign of which is determined by the direction of the surface sensible heat flux,was used to represent the major divisions in climate across the globe,and the usefulness of this approach was evaluated. Five reanalysis datasets and the results of an offline land surface model were investigated. We divided the global continents into five major BRm zones using the climatological means of the sensible and latent heat fluxes during the period 1980–2010:extremely cold,extremely wet,semi-wet,semi-arid and extremely arid. These zones had BRm ranges of(-∞,0),(0,0.5),(0.5,2),(2,10) and(10,+∞),respectively. The climatological mean distribution of the Bowen ratio zones corresponded well with the K ¨oppen-like climate classification,and it reflected well the seasonal variation for each subdivision of climate classification. The features of climate change over the mean climatological BRm zones were also investigated. In addition to giving a map-like classification of climate,the BRm also reflects temporal variations in different climatic zones based on land surface processes. An investigation of the coverage of the BRm zones showed that the extremely wet and extremely arid regions expanded,whereas a reduction in area was seen for the semi-wet and semi-arid regions in boreal spring during the period 1980–2010. This indicates that the arid regions may have become drier and the wet regions wetter over this period of time.

Evaluation of the Forecast Accuracy of Near-Surface Temperature and Wind in Northwest China Based on the WRF Model

This study investigated the performance of the mesoscale Weather Research and Forecasting(WRF) model in predicting near-surface atmospheric temperature and wind for a complex underlying surface in Northwest China in June and December 2015. The spatial distribution of the monthly average bias errors in the forecasts of 2-m temperature and 10-m wind speed is analyzed first. It is found that the forecast errors for 2-m temperature and 10-m wind speed in June are strongly correlated with the terrain distribution. However, this type of correlation is not apparent in December, perhaps due to the inaccurate specification of the surface albedo and freezing-thawing process of frozen soil in winter in Northwest China in the WRF model. In addition, the WRF model is able to reproduce the diurnal variation in 2-m temperature and 10-m wind speed, although with weakened magnitude. Elevations and land-use types have strong influences on the forecast of near-surface variables with seasonal variations. The overall results imply that accurate specification of the complex underlying surface and seasonal changes in land cover is necessary for improving near-surface forecasts over Northwest China.

Impacts of Land-Use Data on the Simulation of Surface Air Temperature in Northwest China

This study examines the impacts of land-use data on the simulation of surface air temperature in Northwest China by the Weather Research and Forecasting(WRF) model. International Geosphere–Biosphere Program(IGBP) landuse data with 500-m spatial resolution are generated from Moderate Resolution Imaging Spectroradiometer(MODIS)satellite products. These data are used to replace the default U.S. Geological Survey(USGS) land-use data in the WRF model. Based on the data recorded by national basic meteorological observing stations in Northwest China, results are compared and evaluated. It is found that replacing the default USGS land-use data in the WRF model with the IGBP data improves the ability of the model to simulate surface air temperature in Northwest China in July and December 2015. Errors in the simulated daytime surface air temperature are reduced, while the results vary between seasons. There is some variation in the degree and range of impacts of land-use data on surface air temperature among seasons. Using the IGBP data, the simulated daytime surface air temperature in July 2015 improves at a relatively small number of stations, but to a relatively large degree; whereas the simulation of daytime surface air temperature in December 2015 improves at almost all stations, but only to a relatively small degree(within 1°C). Mitigation of daytime surface air temperature overestimation in July 2015 is influenced mainly by the change in ground heat flux. The modification of underestimated temperature comes mainly from the improvement of simulated net radiation in December 2015.