An Assessment of the Impact of Land Thermal Infrared Observation on Regional Weather Forecasts Using Two Different Data Assimilation Approaches.

Recent studies have shown the unique value of satellite-observed land surface thermal infrared (TIR) information (e.g., skin temperature) and the feasibility of assimilating land surface temperature (LST) into land surface models (LSMs) to improve the simulation of land-atmosphere water and energy exchanges. In this study, two different types of LST assimilation techniques are implemented and the benefits from the techniques are compared. One of the techniques is to directly assimilate LST using ensemble Kalman filter (EnKF) data assimilation (DA) utilities. The other is to use the Atmosphere-Land Exchange Inversion model (ALEXI) as an "observation operator" that converts LST retrievals into the soil moisture (SM) proxy based on the ratio of actual to potential evapotranspiration (fPET), which is then assimilated into an LSM. While most current studies have shown some success in both directly the assimilating LST and assimilating ALEXI SM proxy into offline LSMs, the potential impact of the assimilation of TIR information through coupled numerical weather prediction (NWP) models is unclear. In this study, a semi-coupled Land Information System (LIS) and Weather Research and Forecast (WRF) system is employed to assess the impact of the two different techniques for assimilating the TIR observations from NOAA GOES satellites on WRF model forecasts. The NASA LIS, equipped with a variety of LSMs and advanced data assimilation tools (e.g., the ensemble Kalman Filter (EnKF)), takes atmospheric forcing data from the WRF model run, generates updated initial land surface conditions with the assimilation of either LST- or TIR-based SM and returns them to WRF for initializing the forecasts. The WRF forecasts using the daily updated initializations with the TIR data assimilation are evaluated against ground weather observations and re-analysis products. It is found that WRF forecasts with the LST-based SM assimilation have better agreement with the ground weather observations than those with the direct LST assimilation or without the land TIR data assimilation.

[Nitrous oxide flux at the water-air interface of the rivers in Nanjing during summer].

Employing floating static chamber-chromatography method, the N2O diurnal fluxes at the water-air interface of four rivers (Tuanjie River, Jinchuan River, Inner and Outer Qinhuai River) and Jinniu Lake were monitored in Nanjing during summer. The results show that four rivers act as the sources of N2O emission, but Jinniu Lake is characterized by the absorption of N2O. The highest N2O flux from Inner Qinhuai presented at 20:00 because of the changing of hydrodynamic conditions. Both Jinchuan and Tuanjie rivers' minimum N2O fluxes were detected when the content of dissolved oxygen was extremely low. The tendency of N2O from Outer Qinhuai showed a double-peak because of its daytime nitrification and nocturnal denitrification. The flux of N2O from Jinniu Lake had been noted as being generally higher at night than that during light hours due to the effect of wind. For natural rivers, the proper sampling period is from 08:00 to 12:00, but for the river subjected to interference, the sampling period is different.

An analysis of influential factors on outdoor thermal comfort in summer.

A variety of research has linked high temperature to outdoor thermal comfort in summer, but it remains unclear how outdoor meteorological environments influence people's thermal sensation in subtropical monsoon climate areas, especially in China. In order to explain the process, and to better understand the related influential factors, we conducted an extensive survey of thermally comfortable conditions in open outdoor spaces. The goal of this study was to gain an insight into the subjects' perspectives on weather variables and comfort levels, and determine the factors responsible for the varying human thermal comfort response in summer. These perceptions were then compared to actual ambient conditions. The database consists of surveys rated by 205 students trained from 6:00 am to 8:00 pm outdoors from 21 to 25 August 2009, at Nanjing University of Information Science & Technology (NUIST), Nanjing, China. The multiple regression approach and simple factor analysis of variance were used to investigate the relationships between thermal comfort and meteorological environment, taking into consideration individual mood, gender, level of regular exercise, and previous environmental experiences. It was found that males and females have similar perceptions of maximum temperature; in the most comfortable environment, mood appears to have a significant influence on thermal comfort, but the influence of mood diminishes as the meteorological environment becomes increasingly uncomfortable. In addition, the study confirms the strong relationship between thermal comfort and microclimatic conditions, including solar radiation, atmospheric pressure, maximum temperature, wind speed and relative humidity, ranked by importance. There are also strong effects of illness, clothing and exercise, all of which influence thermal comfort. We also find that their former place of residence influences people's thermal comfort substantially by setting expectations. Finally, some relationships between thermal perception and amount of exercise, thermal experience, mood, clothing, illness and microclimate, etc., are established. Our findings also shed light on how to resist or adapt to outdoor hyperthermic conditions during summer in subtropical monsoon climate areas.