Kaicun Wang

Clear sky visibility has decreased over land globally from 1973 to 2007.

Visibility in the clear sky is reduced by the presence of aerosols, whose types and concentrations have a large impact on the amount of solar radiation that reaches Earths surface. Here we establish a global climatology of inverse visibilities over land from 1973 to 2007 and interpret it in terms of changes in aerosol optical depth and the consequent impacts on incident solar radiation. The aerosol contribution to “global dimming,” first reported in terms of strong decreases in measured incident solar radiation up to the mid-1980s, has monotonically increased over the period analyzed. Since that time, visibility has increased over Europe, consistent with reported European “brightening,” but has decreased substantially over south and east Asia, South America, Australia, and Africa, resulting in net global dimming over land.

Review on Estimation of Land Surface Radiation and Energy Budgets From Ground Measurement, Remote Sensing and Model Simulations

Land surface radiation and energy budgets are critical components of any land surface models that characterize hydrological, ecological and biogeochemical processes. The estimates of their components generated from remote sensing data or simulations from numerical models have large uncertainties. This paper provides a comprehensive review of recent advances in estimating insolation, albedo, clear-sky longwave downward and upwelling radiation, all-wave net radiation and evapotranspiration from ground measurements, remote sensing algorithms and products, as well as numerical model simulations. The decadal variations of these components are also discussed.

A simple method to estimate actual evapotranspiration from a combination of net radiation, vegetation index, and temperature

Satellite remote sensing is a promising technique for estimating global or regional evapotranspiration (ET). A simple and accurate method is essential when estimating ET using remote sensing data. Such a method is investigated by taking advantage of satellite measurements and the extensive ground-based measurements available at eight enhanced surface facility sites located throughout the Southern Great Plains (SGP) area of the United States from January 2002 to May 2005. Data analysis shows that correlation coefficients between ET and surface net radiation are the highest, followed by temperatures (air temperature or land surface temperature, Ts), and vegetation indices (enhanced vegetation index (EVI) or normalized difference vegetation index (NDVI)). A simple regression equation is proposed to estimate ET using surface net radiation, air or land surface temperatures and vegetation indices. ET can be estimated using daytime-averaged air temperature and EVI with a root mean square error (RMSE) of ~30 W m?2 and a correlation coefficient of 0.91 across all sites and years. ET can also be estimated with comparable accuracy using NDVI and Ts. More importantly, the daytime-averaged ET can also be estimated using only one measurement per day of temperatures (the daytime maximum air temperature or Ts) with comparable accuracy. A sensitivity analysis shows that the proposed method is only slightly sensitive to errors of temperatures, vegetation indices and net surface radiation. An independent validation was made using the measurements colleted by the eddy covariance method at six AmeriFlux sites throughout the United States from 2001 to 2006. The land cover associated with the AmeriFlux sites varies from grassland, to cropland and forest. The results show that ET can be reasonably predicted with a correlation coefficient that varies from 0.84 to 0.95 and a bias that varies from 3 W m?2 to 15 W m?2 and RMSE varying from ~30 W m?2 to ~40 W m?2. The positive bias partly comes from the energy imbalance problem encountered in the eddy covariance method. The proposed method can predict ET under a wide range of soil moisture contents and land cover types.

Estimation of surface long wave radiation and broadband emissivity using Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature//emissivity products

The Moderate Resolution Imaging Spectroradiometer (MODIS) global land surface temperature (LST)/emissivity products supply daily, 8-day, and monthly global temperature and narrowband emissivity data. This article uses these products to calculate the surface long wave radiation of natural objects such as sand, soil, vegetation, etc., based on the Planck function and the Stefan-Boltzmann law. The results show that using the narrowband emissivity of a single band instead of the broadband emissivity results in large errors of up to 100 W m?2 of the calculated long wave radiation. A method to calculate broadband emissivity in the entire TIR spectral region from the narrowband emissivities of the MODIS bands (29, 31, and 32) in the thermal infrared region is proposed. Using the broadband emissivity, the surface long wave radiation could be calculated to an accuracy better than 6 W m?2 in the temperature region of 240–330 K, with a standard deviation of 1.22 W m?2, and a maximum error of 6.05 W m?2 (not considering the uncertainty associated with the MODIS LST/emissivity products themselves). The satellite estimated broadband emissivity was compared with 3-year (January 2001 to December 2003) ground-based measurements of emissivity at Gaize (32.30°N, 84.06°E, 4420 m) on the western Tibetan Plateau. The results show that the broadband emissivity calculated from MODIS narrowband emissivities by this method matches well the ground measurements, with a standard deviation of 0.0085 and a bias of 0.0015.

Aerosol and Monsoon Climate Interactions over Asia

The increasing severity of droughts/floods and worsening air quality from increasing aerosols in Asia monsoon regions are the two gravest threats facing over 60% of the world population living in Asian monsoon regions. These dual threats have fueled a large body of research in the last decade on the roles of aerosols in impacting Asian monsoon weather and climate. This paper provides a comprehensive review of studies on Asian aerosols, monsoons, and their interactions. The Asian monsoon region is a primary source of emissions of diverse species of aerosols from both anthropogenic and natural origins. The distributions of aerosol loading are strongly influenced by distinct weather and climatic regimes, which are, in turn, modulated by aerosol effects. On a continental scale, aerosols reduce surface insolation and weaken the land-ocean thermal contrast, thus inhibiting the development of monsoons. Locally, aerosol radiative effects alter the thermodynamic stability and convective potential of the lower atmosphere leading to reduced temperatures, increased atmospheric stability, and weakened wind and atmospheric circulations. The atmospheric thermodynamic state, which determines the formation of clouds, convection, and precipitation, may also be altered by aerosols serving as cloud condensation nuclei or ice nuclei. Absorbing aerosols such as black carbon and desert dust in Asian monsoon regions may also induce dynamical feedback processes, leading to a strengthening of the early monsoon and affecting the subsequent evolution of the monsoon. Many mechanisms have been put forth regarding how aerosols modulate the amplitude, frequency, intensity, and phase of different monsoon climate variables. A wide range of theoretical, observational, and modeling findings on the Asian monsoon, aerosols, and their interactions are synthesized. A new paradigm is proposed on investigating aerosol-monsoon interactions, in which natural aerosols such as desert dust, black carbon from biomass burning, and biogenic aerosols from vegetation are considered integral components of an intrinsic aerosol-monsoon climate system, subject to external forcing of global warming, anthropogenic aerosols, and land use and change. Future research on aerosol-monsoon interactions calls for an integrated approach and international collaborations based on long-term sustained observations, process measurements, and improved models, as well as using observations to constrain model simulations and projections.

Influences of urbanization on surface characteristics as derived from the Moderate-Resolution Imaging Spectroradiometer: A case study for the Beijing metropolitan area

Moderate-Resolution Imaging Spectroradiometer (MODIS) global land surface temperature/emissivity (LST), vegetation indices, BRDF/Albedo and land cover products collected for the period of March 2000 to March 2006 are combined with the surface heat fluxes retrieved from MODIS as well as meteorological data to investigate the influence of urbanization associated with the surface characteristics of the city of Beijing. The results show that the use of different rural areas in the urban heat island (UHI) calculation influences the value of UHI and its seasonal variation. Daytime UHI shows a distinct seasonal variation, the maximum during summer being larger than 10°C, while conspicuous negative UHI occurs in winter and spring. Seasonal variation of nighttime UHI is much less. The contrast in thermal inertia between rural and urban areas, anthropogenic heat from the urban area and less latent heat flux over urban areas are the main factors influencing daytime UHI, whereas anthropogenic heat controls the nighttime UHI. Surface broadband emissivity derived from MODIS LST/emissivity for the urban area is nearly equal to the rural areas. Surface albedo over the urban area is 0.03–0.08 less than that of rural areas, but aerosols substantially reduce surface incoming solar radiation over the urban area, which results in the surface absorbed solar radiation being nearly equal for urban and rural areas during autumn. Diurnal variation of UHI demonstrates a distinctively seasonal variation. The accuracy of MODIS LST is investigated and it was found that the influence of satellite view angle on the calculated UHI is small enough to be ignored.

Contribution of solar radiation to decadal temperature variability over land

Significance Global air temperature has become the primary metric for judging global climate change. The variability of global temperature on a decadal timescale is still poorly understood. This paper shows that surface incident solar radiation (Rs) over land globally peaked in the 1930s, substantially decreased from the 1940s to the 1970s, and changed little after that. The cooling effect of this reduction of Rs accounts in part for the near-constant temperature from the 1930s into the 1970s. Since then, neither the rapid increase in temperature from the 1970s through the 1990s nor the slowdown of warming in the early twenty-first century appear to be significantly related to changes of Rs. Global air temperature has become the primary metric for judging global climate change. The variability of global temperature on a decadal timescale is still poorly understood. This paper examines further one suggested hypothesis, that variations in solar radiation reaching the surface (Rs) have caused much of the observed decadal temperature variability. Because Rs only heats air during the day, its variability is plausibly related to the variability of diurnal temperature range (daily maximum temperature minus its minimum). We show that the variability of diurnal temperature range is consistent with the variability of Rs at timescales from monthly to decadal. This paper uses long comprehensive datasets for diurnal temperature range to establish what has been the contribution of Rs to decadal temperature variability. It shows that Rs over land globally peaked in the 1930s, substantially decreased from the 1940s to the 1970s, and changed little after that. Reduction of Rs caused a reduction of more than 0.2 °C in mean temperature during May to October from the 1940s through the 1970s, and a reduction of nearly 0.2 °C in mean air temperature during November to April from the 1960s through the 1970s. This cooling accounts in part for the near-constant temperature from the 1930s into the 1970s. Since then, neither the rapid increase in temperature from the 1970s through the 1990s nor the slowdown of warming in the early twenty-first century appear to be significantly related to changes of Rs.

Developed and developing world responsibilities for historical climate change and CO2 mitigation

At the United Nations Framework Convention on Climate Change Conference in Cancun, in November 2010, the Heads of State reached an agreement on the aim of limiting the global temperature rise to 2 °C relative to preindustrial levels. They recognized that long-term future warming is primarily constrained by cumulative anthropogenic greenhouse gas emissions, that deep cuts in global emissions are required, and that action based on equity must be taken to meet this objective. However, negotiations on emission reduction among countries are increasingly fraught with difficulty, partly because of arguments about the responsibility for the ongoing temperature rise. Simulations with two earth-system models (NCAR/CESM and BNU-ESM) demonstrate that developed countries had contributed about 60–80%, developing countries about 20–40%, to the global temperature rise, upper ocean warming, and sea-ice reduction by 2005. Enacting pledges made at Cancun with continuation to 2100 leads to a reduction in global temperature rise relative to business as usual with a 1/3–2/3 (CESM 33–67%, BNU-ESM 35–65%) contribution from developed and developing countries, respectively. To prevent a temperature rise by 2 °C or more in 2100, it is necessary to fill the gap with more ambitious mitigation efforts.

Validation of the MODIS global land surface albedo product using ground measurements in a semidesert region on the Tibetan Plateau

An evaluation of the Moderate-Resolution Imaging Spectroradiometer (MODIS) global land surface albedo product is essential for its use in scientific studies. We evaluate the accuracy of the albedo product with nearly 3 years (from January 2001 to July 2003) of ground measurements from the Gaize Automatic Weather Station (32.30°N, 84.06°E, 4420 m) on the western Tibetan Plateau. The land surface consists of semidesert or desert soil. Vegetation in this region is very rare. A comparison with field measurements shows that the MODIS global land surface albedo meets an absolute accuracy requirement of 0.02. There is no distinctive bias between the MODIS-derived albedo and the ground-measured albedo, with a root-mean-square error of 0.0186 and a maximum error of 0.036.

Evaluation and improvement of the MODIS land surface temperature/emissivity products using ground-based measurements at a semi-desert site on the western Tibetan Plateau

Current MODerate‐resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST, surface skin temperature)/emissivity products are evaluated and improvements are investigated. The ground‐based measurements of LST at Gaize (32.30° N, 84.06° E, 4420 m) on the western Tibetan Plateau from January 2001 to December 2002 agree well (mean and standard deviation of differences of 0.27 K and 0.84 K) with the 1‐km Version 004 (V4) Terra MODIS LST product (MOD11A1) generated by the split‐window algorithm. Spectral emissivities measured from surface soil samples collected at and around the Gaize site are in close agreement with the landcover‐based emissivities in bands 31 and 32 used by the split‐window algorithm. The LSTs in the V4 MODIS LST/emissivity products (MYD11B1 for Aqua and MOD11B1 for Terra) from the day/night LST algorithm are higher by 1–1.7 K (standard deviation around 0.6 K) in comparisons to the 5‐km grid aggregated values of the LSTs in the 1‐km products, which is consistent with the results of a comparison of emissivities. On average, the emissivity in MYD11B1 (MOD11B1) is 0.0107 (0.0167) less than the ground‐based measurements, which is equivalent to a 0.64 K (1.25 K) overestimation of LST around the average value of 285 K. Knowledge obtained from the evaluation of MODIS LST/emissivity retrievals provides useful information for the improvement of the MODIS LST day/night algorithm. Improved performance of the refined (V5) day/night algorithm was demonstrated with the Terra MODIS data in May–June 2004.