[1] Warming climates have been widely recognized to advance spring vegetation phenology. However, the delayed responses of vegetation phenology to rising temperature and their mechanisms are poorly understood. Using satellite and climate data from 1982 to 2005, we reveal a latitude transition zone of greenup onset in vegetation communities that has diversely responded to warming temperature in North America. From 40°N northwards, a winter chilling requirement for vegetation dormancy release is far exceeded and the decrease in chilling days by warming winter temperature has little impact on thermal-time requirements for greenup onset. Thus, warming spring temperature has constantly advanced greenup onset by 0.32 days/year. However, from 40°N southward, the shortened winter chilling days are insufficient for fulfilling vegetation chilling requirement, so that the thermal-time requirement for greenup onset during spring increases gradually. Consequently, vegetation greenup onset changes progressively from an early trend (north region) to a later trend (south region) along the latitude transition zone from 40-31°N, where the switch occurs around 35°N. The greenup onset is delayed by 0.15 days/year below 31°N.

[1] The measurements from microwave sounding unit (MSU) on board different NOAA polar-orbiting satellites have been extensively used for detecting atmospheric temperature trend during the last several decades. However, temperature trends derived from these measurements are under significant debate, mostly caused by calibration errors. This study recalibrates the MSU channel 2 observations at level 0 using the postlaunch simultaneous nadir overpass (SNO) matchups and then provides a well-merged new MSU 1b data set for climate studies. The calibration algorithm consists of a dominant linear response of the MSU raw counts to the Earth-view radiance plus a smaller quadratic term. Uncertainties are represented by a constant offset and errors in the coefficient for the nonlinear quadratic term. A SNO matchup data set for nadir pixels with criteria of simultaneity of less than 100 s and within a ground distance of 111 km is generated for all overlaps of NOAA satellites. The simultaneous nature of these matchups eliminates the impact of orbital drifts on the calibration. A radiance error model for the SNO pairs is developed and then used to determine the offsets and nonlinear coefficients through regressions of the SNO matchups. It is found that the SNO matchups can accurately determine the differences of the offsets as well as the nonlinear coefficients between satellite pairs, thus providing a strong constraint to link calibration coefficients of different satellites together. However, SNO matchups alone cannot determine the absolute values of the coefficients because there is a high degree of colinearity between satellite SNO observations. Absolute values of calibration coefficients are obtained through sensitivity experiments, in which the percentage of variance in the brightness temperature difference time series that can be explained by the warm target temperatures of overlapping satellites is a function of the calibration coefficient. By minimizing these percentages of variance for overlapping observations, a new set of calibration coefficients is obtained from the SNO regressions. These new coefficients are significantly different from the prelaunch calibration values, but they result in bias-free SNO matchups and near-zero contaminations by the warm target temperatures in terms of the calibrated brightness temperature. Applying the new calibration coefficients to the Level 0 MSU observations, a well-merged MSU pentad data set is generated for climate trend studies. To avoid errors caused by small SNO samplings between NOAA 10 and 9, observations only from and after NOAA 10 are used. In addition, only ocean averages are investigated so that diurnal cycle effect can be ignored. The global ocean-averaged intersatellite biases for the pentad data set are between 0.05 and 0.1 K, which is an order of magnitude smaller than that obtained when using the unadjusted calibration algorithm. The ocean-only anomaly trend for the combined MSU channel 2 brightness temperature is found to be 0.

Clear and cloudy daytime comparisons of land surface temperature (LST) and air temperature (Tair) were made for 14 stations included in the U.S. Climate Reference Network (USCRN) of stations from observations made from 2003 through 2008. Generally, LST was greater than Tair for both the clear and cloudy conditions; however, the differences between LST and Tair were significantly less for the cloudy-sky conditions. In addition, the relationships between LST and Tair displayed less variability under the cloudy-sky conditions than under clear-sky conditions. Wind speed, time of the observation of Tair and LST, season, the occurrence of precipitation at the time of observation, and normalized difference vegetation index values were all considered in the evaluation of the relationship between Tair and LST. Mean differences between LST and Tair of less than 28C were observed under cloudy conditions for the stations, as compared with a minimum difference of greater than 28C (and as great as 718C) for the clear-sky conditions. Under cloudy conditions, Tair alone explained over 94%-and as great as 98%-of the variance observed in LST for the stations included in this analysis, as compared with a range of 81%-93% for clear-sky conditions. Because of the relatively homogeneous land surface characteristics encouraged in the immediate vicinity of USCRN stations, and potential regional differences in surface features that might influence the observed relationships, additional analyses of the relationships between LST and Tair for additional regions and land surface conditions are recommended.

[1] The long-term trend of aerosol optical thickness (AOT) over the global oceans has been studied by using a nearly 25-year aerosol record from the Advanced Very High Resolution Radiometer (AVHRR) Pathfinder Atmosphere extended (PATMOS-x) data set. Both global and regional analyses have been performed to derive the AOT tendencies for monthly, seasonal, and annual mean AOT values at AVHRR 0.63 mm channel (or Channel-1). A linear decadal change of À0.01 is obtained for globally and monthly averaged aerosol optical thickness, t 1 , of AVHRR Channel-1. This negative tendency is even more evident for globally and annually averaged t 1 and the magnitude can be up to À0.03/decade. Seasonal patterns in the AOT regional long-term trend are evident. In general, negative tendencies are observed for seasonally averaged t 1 in regions influenced by emissions from industrialized countries and the magnitude can be up to À0.10/decade. Positive tendencies are observed in regions influenced by emissions from fast developing countries and the magnitude can be up to +0.04/decade. For regions heavily influenced by Saharan desert particles, a negative trend with a maximum magnitude of À0.03/decade is detected. However, over regions influenced by smoke from biomass burning, positive tendencies with a maximum magnitude of +0.04/decade are observed. Sensitivity analyses have also been performed to study the effects of radiance calibration, aerosol retrieval algorithm, and spatial resolution of input retrieval radiances on the global aerosol long-term tendencies.