Search

We investigated the interannual variations in the annual mean and seasonal cycle of upward shortwave radiation at the top of atmosphere (TOA SW↑) over the Arctic using the Clouds and the Earth’s Radiant Energy System (CERES) observation data during 2001–2020. The annual mean TOA SW↑ over the Arctic showed a decreasing trend from 2001 to 2012 (−2.5 W m−2 decade−1) and had a large interannual variability after 2012. The standard deviation of detrended TOA SW↑ increased from 0.4 W m−2 in 2001–2012 to 1.1 W m−2 in 2012–2020. Over land, TOA SW↑ variation was related to snow cover in May, snow cover, cloud fraction, and cloud optical depth (COD) in June, and cloud fraction and COD in July. Over ocean, TOA SW↑ variation in June and July was linked to sea ice cover. TOA SW↑ variation over ocean in June and July after 2012 was highly related to the North Atlantic Oscillation (NAO). This study suggests that changes in the large annual mean TOA SW↑ variability after 2012 is explained by the timing of land snow and sea ice melt in spring and summer, and cloud variability over land in summer.

The Second-generation Global Imager (SGLI) onboard the Global Change Observation Mission – Climate (GCOM-C) satellite launched on December 23, 2017, observes various geophysical parameters with the aim of a better understanding of the global climate system. As part of that aim, SGLI has great potential to unravel several uncertainties related to clouds by providing new cloud products along with several other atmospheric products related to cloud climatology, including aerosol products from polarization channels. However, a very little is known about the quality of the SGLI cloud products. This study uses data about clouds and global irradiances observed from the Earth’s surface using a sky radiometer and a pyranometer, respectively, to understand the quality of the two most fundamental cloud properties—cloud optical depth (COD) and cloud-particle effective radius (CER)—of both water and ice clouds. The SGLI-observed COD agrees well with values observed from the surface, although it agrees better for water clouds than for ice clouds, while the SGLI-observed CER exhibits poorer agreement than does the COD, with the SGLI values being generally higher than the sky radiometer values. These comparisons between the SGLI and sky radiometer cloud properties are found to differ for different cloud types of both the water and ice cloud phases and different solar and satellite viewing angles by agreeing better for relatively uniform and flat cloud type and for relatively low solar zenith angle. Analyses of SGLI-observed reflectance functions and values calculated by assuming plane-parallel cloud layers suggest that SGLI-retrieved cloud properties can have biases on the solar and satellite viewing angles, similar to other satellite sensors including the Moderate Resolution Imaging Spectroradiometer (MODIS). Furthermore, it is found that the SGLI-observed cloud properties reproduce global irradiances quite satisfactorily for both water and ice clouds by resembling several important features of the COD comparison, such as the better agreement for water clouds than for ice clouds and the tendency to underestimate (resp. overestimate) the COD in SGLI observations for optically thick (resp. thin) clouds.

Low-level cloud plays a key role in modulating air–sea interaction processes and sea surface temperature (SST) variability. The present study investigated the evolution process of oceanic low-level cloud cover (LCC) and related air–sea interaction processes on an intraseasonal time scale in the summertime (June–October) North Pacific (30°–40°N, 165°–175°E) based on satellite observational and reanalysis datasets from 2003 to 2016. The intraseasonal time scale (20–100 days) is dominant not only for the LCC, but also for LCC controlling factors, that is, SST, estimated inversion strength (EIS), and horizontal temperature advection (Tadv). To reveal the lead–lag relationship among these variables, we conducted phase composite analysis with a bandpass filter based on the intraseasonal variability (ISV) of LCC. It suggests that ISV of LCC leads to that of SST and that horizontal dry–cold advection from the poleward region leads to increasing LCC and decreasing SST. The increasing LCC corresponds to a positive relative humidity (RH) anomaly in the lower troposphere, which is due to adiabatic cooling with shallow convection, vertical moisture advection, and meridional RH advection associated with the anomalous cold Tadv. Heat budget analysis of the ocean mixed layer suggests the importance of anomalous dry–cold advection for cooling SST, not only via enhanced latent heat release but also via decreased downward shortwave radiation at the sea surface according to cloud radiative effect with a positive LCC anomaly. Determining the detailed lead–lag relationship between LCC and its controlling factor is a good approach to understand mechanisms of the local processes of both low-level cloud evolution and air–sea interaction.

Wildfires damage land ecosystems and significantly impact the atmosphere by releasing large amounts of CO2 and aerosols. Aerosols, in particular, have a radiative forcing potential that perturbs the global radiation balance. Therefore, understanding their optical properties is essential to estimate the radiative forcing for predicting the climatic impact due to burning. The Global Change Observation Mission—Climate, or GCOM-C (SHIKISAI), is a polar-orbit satellite launched by JAXA on 23 December 2017. This study analyzed wildfires in the Amazon, Angola, Australia, California, Siberia, and Southeast Asia that occurred after 2018 using data from the GCOM-C satellite obtained with the Second-generation Global Imager (SGLI), a multi-band optical imaging radiometer. We compared the aerosol optical properties of Ångström Exponent (AE) and Single Scattering Albedo (SSA) and found that their distributions are different for each region. In addition, the negative correlations are found in the Amazon, Angola, Siberia, and Southeast Asia when we locally fitted the AE and SSA relationship for each wildfire by a linear function. This is likely due to the effect of hygroscopic growth (SSA becomes larger with water uptake), considering the difference in relative humidity in the six regions, and the significant behavior of the aerosol aging. We also found that the relationship between SSA and relative humidity varies depending on the type of the burned vegetation. For the needle-forest-dominated group, a higher SSA is observed in the range from 40 % to 70 % of relative humidity than the broad forest-dominated group. This global investigation of the aerosol optical properties reveals that their characteristics differ due to regional differences such as relative humidity and vegetation type. Thus, the regional characteristics and the aging effect of biomass-burning aerosols must be considered in model predicting. Moreover, we estimated the net incoming radiation at the top of the atmosphere during the intense fire periods to understand the impact of the direct effect of biomass burning aerosols on radiative forcing. The estimates show a significant negative radiative forcing (i.e., a cooling effect) over the ocean (−78 and −96 Wm−2 in Australia and California, respectively). In contrast, small values are observed over land (∼ −10 Wm−2 for all six regions). This suggests that the radiative forcing depends on the region of the wildfire plumes. Therefore, taking the regional characteristics of the optical property and surface reflectance into account is necessary to estimate the effect on radiative forcing and future impacts of a short-lived climate forcer from wildfires.

Aerosols emitted in densely populated and industrialized Indo‐Gangetic Plain, one of the most polluted regions in the world, modulate regional climate, monsoon, and Himalayan glacier retreat. Thus, this region is important for understanding aerosol perturbations and their resulting impacts on atmospheric changes during COVID‐19 lockdown period, a natural experimental condition created by the pandemic. By analyzing 5 years (2016–2020) data of aerosols and performing a radiative transfer calculation, we found that columnar and near‐surface aerosol loadings decreased, leading to reductions in radiative cooling at the surface and top of the atmosphere and atmospheric warming during lockdown period. Further, satellite data analyses showed increases in cloud optical thickness and cloud‐particle effective radius and decrease in lower tropospheric air temperature during lockdown period. These results indicate critical influences of COVID‐19 lockdown on regional climate and water cycle over Indo‐Gangetic Plain, emphasizing need for further studies from modeling perspectives., Key Points Aerosols reduced by COVID‐19 lockdown perturbed atmospheric heat budget over the Indo‐Gangetic PlainCloud optical thickness and cloud‐particle effective radius increased during COVID‐19 lockdown periodAir temperature in the lower troposphere decreased during COVID‐19 lockdown period

An optimal estimation algorithm to retrieve the cloud optical depth (COD) and cloud particle effective radius (CER) from spectral zenith radiances observed by narrow field-of-view (FOV) ground-based sky radiometers was developed. To further address the filter degradation problem while analyzing long-term observation data, an on-site calibration procedure is proposed, which has good accuracy compared with the standard calibration transfer method. An error evaluation study conducted by assuming errors in observed transmittances and ancillary data for water vapor concentration and surface albedo suggests that the errors in input data affect retrieved CER more than COD. Except for some narrow domains that fall within a COD of

An optimal-estimation based algorithm to retrieve cloud optical thickness (COD) and cloud-particle effective radius (CER) from spectral zenith radiances observed by a narrow field of view (FOV) ground-based sky radiometer is developed. To further address the filter-degradation problem while analyzing data of long-term observation, an on-site calibration procedure is proposed, which is found to have a very good accuracy with respect to a standard procedure, i.e., a procedure of deriving calibration constants using a master instrument. An error evaluation study conducted by assuming errors in observation-based transmittances and ancillary data of water vapor concentration and surface albedo suggests that the errors in input data can influence retrieved CER more effectively than COD. Except for some narrow domains that fall within COD&thinsp

The stringent control measures in China to curb the spread of Coronavirus disease (COVID-19) have had profound societal and environmental impacts, including changes in energy consumption practices and thereby in air pollutant emissions. In this study, a suite of satellite and numerically assimilated air pollution and meteorological data combined with information on energy consumption practices and nighttime light (NTL) was used to evaluate the effects of these COVID-19 control measures on air quality. These data revealed that control measures reduced aerosols mostly over central and eastern parts of China by countering favorable meteorological conditions for increased aerosols. The control measures reduced short-lived nitrogen dioxide (NO2) with little influence on long-lived carbon monoxide (CO). Consistent with energy production and energy consumption statistics in different sectors, NTL data suggest that high human mobility within the residential sector and reduced activity in other sectors during the implementation of control measures explain small but significant decreases in black carbon and sulfate aerosols, respectively, during this period. Overall, these results provide useful information for policy makers and the scientific community by clarifying the contributions of meteorological factors and energy consumption to changes in air quality. This information can guide the development of air pollution mitigation strategies and provides insight into the air pollution status in China and the potential for long-distance transport. © The Author(s).

Lockdown measures have been adopted in many countries worldwide due to the onset of the COVID-19 pandemic, including in Thailand. Air quality improvements with regard to restrictions of daily movement among Bangkok people have been reported. This study explores the impact of the COVID-19 outbreak and long-range pollution on air quality in Bangkok Metropolitan, Thailand by using ground-based and satellite measurements such as MODIS and TROPOMI data. Moreover, the results project some possible future trends of air quality in Bangkok Metropolitan. The 24-hr average concentrations of PM2.5, O3, NO2, CO and SO2 were compared between the periods of Normal, Lockdown and New Normal. PM2.5 concentrations increased by 20.56% during the Normal period and decreased by –15.79% and –23.34% during the Lockdown and New Normal periods, respectively, compared to the same periods in 2017–2019. There were also significant decreasing trends in O3: –7.13% and 4.72%; and CO: –8.01% and 23.59% during the Lockdown and New Normal periods, respectively, while NO2 and SO2 concentrations showed increasing trends during the three periods. The MODIS and TROPOMI data analyses indicate the COVID-19 outbreak has had significant positive impact on surface pollution, but no impact on upper atmospheric pollution due to added pollution from long-range transport. The results also demonstrate that surface air pollution had a combination effect from biomass burning, traffic, industrial and household sources during the Lockdown period, except for SO2 concentrations, which were attributed to long-range transport pollution loading. In some cases, a negative impact of the COVID-19 lockdown on air pollution can be observed due to certain activities increasing within Bangkok Metropolitan. Additionally, the results also show that changing the lifestyle into a “new normal” for people in Bangkok after the Lockdown period has had a positive effect on air pollution.

Observations of downward radiative flux at the sea surface generally contain uncertainty due to limited numbers of observations and limitations of auxiliary equipment. The lack of shading from direct solar radiation and ventilation systems causes bias or random errors. To evaluate the error of radiation measurements at buoys, downward shortwave and longwave radiative fluxes are compared with International Satellite Cloud Climatology Project (ISCCP), Japanese 55-year Reanalysis (JRA55), and Moderate Resolution Imaging Spectroradiometer (MODIS) retrieved model calculations of 3-h and daytime averages. Cloud masking is evaluated by a combination of MTSAT-1R and in situ observations. Coincident observations from a land-surface station located near the buoy observatories are compared with satellite and reanalysis products. The bias at buoys, compared with retrievals, approximately over- and under-estimate for longwave and shortwave fluxes, respectively. The bias at buoys is larger and smaller than the land by 23–34 W m−2 for longwave and 13–51 W m−2 for shortwave radiation using 3-h averages under clear-sky conditions. The differences in bias decrease when using daytime averages for longwave, but the difference for shortwave increases with daytime averages. To evaluate the effect of environmental factors on buoy observations, we compared rainfall, wind speed, and solar zenith angle with the biases. We found that rainfall and wind speed affect buoy pyrgeometers such that they overestimate the longwave flux. The cosine of solar zenith angle does not cause overestimation for longwave flux, and the effect of dome heating is small. The strong wind causes underestimation of the shortwave radiative flux due to tilting. The effect of wind is reduced when daily averages are used.

The dependence of atmospheric particles’ backscattering coefficients (BSCs) on their concentration and constitution in the near surface air at southwestern Japanese coast in the spring of 2011–2015 was investigated. The BSCs were measured with a ceilometer at the wavelength 905 ± 5 nm. The size-segregated concentrations of particles larger than 0.3 µm were measured with optical particle counters. The constitution of particles in each of eight episodes, i.e., the portions of mineral dust, sea salt, sulfate and soot particles, was obtained with individual particle analysis by using an electron microscope. There was a close correlation (R2 = 0.76) between the BSCs and the volume concentrations of the particles when the relative humidity (RH) was lower than ~70%, regardless of the difference in particle constitutions. In contrast, the BSCs normalized with aerosol concentrations differed largely even at similar concentrations of particles when the RH was larger than 70%. The BSCs of particles dominated by marine origin (sea salt) could be several times larger than those dominated by land origin (dust and soot) at 90% RH, as the latter might be slightly larger than the BSCs under the dry conditions. On the other hand, the difference of volume-size distributions of particles likely also made the BSCs largely different from each other under the humid conditions. These results indicate that the concentration of atmospheric particles was the key parameter to determine the BSCs under dry conditions, while the BSCs under humid conditions were closely dependent on the content of deliquescent components and the size distributions of the particles.

This study reviews the role of aerosols in the shortwave radiation budget and climate change in China. As an example of the aerosol radiative effect, the relationship between surface shortwave radiation and aerosol properties is explored. The anthropogenic aerosol, particularly black carbon is important to address long-term variations of surface shortwave radiation in China. Another role of aerosol is its relation to cloud formation and precipitation processes. Cloud condensation is affected by air pollution aerosol, but the aerosol effect on precipitation is not obvious. Quantitative assessment of the aerosol effect on the cloud and precipitation is quite difficult particularly in China as local aerosol has a wide range of chemical and physical properties. The mixture status is also a key factor to understand and predict climate change in the past, present, and future. The improved understanding of aerosols and precursor emissions can aid to resolve some climate change issues.

We revealed the difference in tropical ice cloud microphysical properties between the western Pacific (WP) and the eastern Pacific (EP), based on satellite retrievals. Vertical profile of effective particle radius of ice cloud (re) was estimated from active sensors on board CloudSat and CALIPSO satellites. In this study, we focused only on ice cloud which is defined as clouds with the cloud top temperature lower than 0°C. To investigate the relationship between cloud optical properties and cloud vertical structures, these ice clouds were classified into five types based on cloud optical thickness values. Compared the vertical profile of re in WP with that in the EP, re around the freezing level within convective cloud in EP slightly larger than that in WP. This analysis also shows that re of optically thick cloud is larger than that of optically thin cloud. The difference in re may be caused by differences in moisture convergence, upward motion, aerosols.

This study analyzed the global and seasonal characteristics of cloud phase and ice crystal orientation (CTYPE-lidar) by using the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) on board the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). A dataset from September 2006 to August 2007 was used to derive the seasonal characteristics. The discrimination scheme was originally developed by Yoshida et al., who classified clouds mainly into warm water, supercooled water, and randomly oriented ice crystals or horizontally oriented ice plates. This study used the following products for the comparison with CTYPE-lidar: (i) the vertical feature mask (VFM) of the National Aeronautics and Space Administration (NASA), (ii) the Moderate Resolution Imaging Spectroradiometer (MODIS), and (iii) European Centre for Medium-Range Weather Forecasts (ECMWF). Overall, the results showed that the CTYPE-lidar discrimination scheme was consistent with the outputs from VFM, MODIS, and ECMWF. The zonal mean water cloud cover in daytime from this study showed good agreement with that derived from MODIS; the slope of the linear regression was 1.06 and the offset was 0.002. The CTYPE-lidar ice cloud occurrence frequency and the ECMWF ice supersaturation occurrence frequency were also in good agreement; the slope of the linear regression of the two products was 1.02 in the temperature range −60°C ≤ T ≤ −30°C. The maximum occurrence frequencies in this study and ECMWF were recognized around −60°C of the equator, with their peak shifted from several degrees north (~9°N) in September–November (SON) to south (~9°S) in December–February (DJF) and back to north (~7°N) in March–May (MAM) and June–August (JJA)., 資料番号: PA1510038000

Satellite data were used to investigate maritime-continental differences in the characteristics of the low-level cloud (the Yamase cloud) that covered northeast Japan during the summer of 2003. The features of the Yamase cloud were found to be almost the same as those of general stratus clouds but with a smaller effective radius (re) and a greater optical thickness (τ) over land, as compared with general stratus clouds. The values ofreover land (average, 11.8 μm) were smaller than those over the ocean (13.5 μm), and the values ofτand the cloud water path over land (20 and 145 gm−2, resp.) showed larger spatial variances than those over the ocean (10 and 86 gm−2, resp.), although the cloud top altitude was nearly the same over both ocean and land (1–3 km). We suggest that this maritime-continental contrast is a result of the combined effects of topography and aerosols characteristics. The Yamase wind blowing from the ocean is forced upwards in coastal regions by the steep mountainous terrain. The updraft drives the inhomogeneity in cloud parameters, and a convective-like cloud develops without precipitation. The relationship betweenreandτsuggests high aerosol concentrations and unstable conditions over land.

Aerosol and cloud optical properties are studied using data from ground-based and ship-borne sky radiometer measurements in the world. We are seeking in this data information on the aerosol optical characteristics with respect to their temporal and spatial variability and validation of Satellite and numerical models. The aerosol optical thickness has clear temporal and spatial variability at six sites in Japan. Comparisons between aerosol optical thickness at 0.5 μm retrieved with a sky radiometer and SPRINTAS at six Japan sites. Model of all sky AOT500 is good correlation. But, model of clear sky AOT500C is not good correlation. We will confirm the trends of aerosol climatology and help explain the reason., International Radiation Symposium: Radiation Processes in the Atmosphere and Ocean, IRS 2012; Berlin; Germany; 6 August 2012 ～ 10 August 2012, AIP Conference Proceedings, 1531, pp.284-287; 2013

We developed a method for classifying hydrometeor particle types, including cloud and precipitation phase and ice crystal habit, by a synergistic use of CloudSat/Cloud Profiling Radar (CPR) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)/Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP). We investigated how the cloud phase and ice crystal habit characterized by CALIOP globally relate with radar reflectivity and temperature. The global relationship thus identified was employed to develop an algorithm for hydrometeor type classification with CPR alone. The CPR-based type classification was then combined with CALIPSO-based type characterization to give CPR-CALIOP synergy classification. A unique aspect of this algorithm is to exploit and combine the lidar's sensitivity to thin ice clouds and the radar's ability to penetrate light precipitation to offer more complete picture of vertically resolved hydrometeor type classification than has been provided by previous studies. Given the complementary nature of radar and lidar detections of hydrometeors, our algorithm delivers thirteen hydrometeor types: warm water, supercooled water, randomly-oriented ice crystal (3D-ice), horizontally-oriented plate (2D-plate), 3D-ice+2D-plate, liquid drizzle, mixed-phase drizzle, rain, snow, mixed-phase cloud, water+liquid drizzle, water+rain and unknown. The global statistics of three-dimensional occurrence frequency of each hydrometeor type revealed that 3D-ice contributes the most to the total cloud occurrence frequency (53.8%), followed by supercooled water (14.3%), 2D-plate (9.2%), rain (5.9%), warm water (5.7%), snow (4.8%), mixed-phase drizzle (2.3%), and the remaining types (4.0%). This hydrometeor type classification provides useful observation-based information for climate model diagnostics in representation of cloud phase and their microphysical characteristics.

It is important to clarify the contributions of clouds and aerosols to the variation of surface shortwave irradiance (S) for climatological studies. This study examined the contributions of clouds and aerosols to the variation in S over East Asia (75-135°E, 20-55°N) in July during 2001 and 2007 using the index of potential radiative forcing (PRF) to characterize the temporal and geographical variations. After confirming the validity of PRF for multiyear analyses, we performed several temporal analyses of clouds and aerosols over the whole research domain. Changes in the geographical distribution, contribution histograms, and averaged values were studied. In agreement with previous studies that treated single-year cases, we confirmed that the magnitudes of the temporal changes in S variations due to clouds and aerosols were highly variable geographically. As for domain-averaged S variations, we did not observe defined trends for the research period. It was also found that the temporal variation between one parameter and its S variation was negatively correlated, from the point analyses at two locations. Based on these results, we concluded that PRF is a promising tool for research into long-term S variations. This kind of information will be quite valuable as basic data for use in climate modeling., Journal of Quantitative Spectroscopy and Radiative Transfer, 112(2), pp329-337; 2011

Downward shortwave flux at the surface over China was derived from sunshine duration data using parameters of Jordan sunshine recorders. The sunshine duration data were obtained as routine meteorological data and ad- justed as necessary for the eects of topography, station surroundings, altitude, and atmospheric turbidity. Calculated flux was verified by in situ observations. Daily flux was calculated at more than 190 stations in China, Climatic maps (statistical period: 1971-2000) of surface solar radiation were produced and have been made public. The sunshine duration-based shortwave flux was used to check satellite observation-based datasets. Two ver- sions of satellite-based surface radiation budget datasets (SRB 2.0 and SRB 3.0) from NASA's Langley Research Center were investigated. Compared with the SRB 2.0 dataset, the SRB 3.0 dataset showed improved shortwave flux, especially over western China and the Tibetan Plateau.

Using a recently-proposed index of the potential radiative forcing (PRF), we quantified 2-dimentional relative contributions of atmospheric parameters (clouds, aerosols and precipitable water) on the change of surface shortwave irradiance (S) over East Asia in July from 2003 to 2004. Analyses at some points revealed that contributions of the cloud optical depth, cloud amount and aerosol optical depth took various values, including the sign, depending the combination of atmospheric parameters' values and differences. The contribution of precipitable water was rather small compared to other parameters'. For example, the S change of totally about -70 (W/m2) was estimated in the south China case because of all the negative factors. On the other hand, the S change of nearly 20 (W/m2) was calculated as a result of a small negative aerosol effect and a moderate positive effect by the cloud optical depth in the central China case. Like these cases, PRF is useful in determining which of the parameters has a dominant effect on the overall change in S. Comparison of the summation of each PRF-derived contribution and the difference in S from the ISCCP products were fairly favorable (the correlation coefficient of 0.84). Regardless of a few shortcomings, obtained results demonstrated the usefulness of PRF for various climate investigations. Nonetheless, rigid validation against estimated S changes using PRF should be done with independent observations such as ground-based pyranometer measurements., Atmospheric Research, 96(2-3), pp.337-343; 2010

We have been performing radiative budget measurements at a ground-based observatory located on Fukue Island. In this study, we analyzed the data from instruments installed in the observatory and the data observed by MODIS, the satellite-borne imager, to evaluate cirrus cloud radiative forcing (CRF). The result shows that CRF took a large positive value as 127.98 W m-2 at the top of the atmosphere (TOA) and a small positive value as 13.2 W m-2 at the surface. As a result, it was found that optically very thin cirrus clouds exert a strong warming effect on the Earth's system and a weak warming effect on the Earth's surface when aerosols are not taken into account.

Simultaneous ground-based measurements of ozone (O3) and carbon monoxide (CO) were conducted in March 2005 as part of the East Asian Regional Experiment (EAREX) 2005 under the umbrella of the Atmospheric Brown Clouds (ABC) project. Multiple air quality monitoring networks were integrated by performing intercomparison of individual calibration standards and measurement techniques to ensure comparability of ambient measurements, along with providing consistently high time-resolution measurements of O3 and CO at the surface sites in East Asia. Ambient data collected from eight surface stations were compared with simulation results obtained by a regional chemistry transport model to infer recent changes in CO emissions from East Asia. Our inverse estimates of the CO emissions from China up to 2005 suggested an increase of 16% since 2001, in good agreement with the recent MOPITT satellite observations and the bottom-up estimates up to 2006. The O3 enhancement relative to CO in continental pollution plumes traversed in the boundary layer were examined as a function of transport time from the Asian continent to the western Pacific Ocean. The observed ΔO3/ΔCO ratios show increasing tendency during eastward transport events due likely to en-route photochemical O3 formation, suggesting that East Asia is an important O3 source region during spring.

Solar radiation is one of the most important factors affecting climate and the environment. Routine measurements of irradiance are valuable for climate change research because of long time series and areal coverage. In this study, a set of quality assessment (QA) algorithms is used to test the quality of daily solar global, direct, and diffuse radiation measurements taken at 122 observatories in China during 1957–2000. The QA algorithms include a physical threshold test (QA1), a global radiation sunshine duration test (QA2), and a standard deviation test applied to time series of annually averaged solar global radiation (QA3). The results show that the percentages of global, direct, and diffuse solar radiation data that fail to pass QA1 are 3.07%, 0.01%, and 2.52%, respectively; the percentages of global solar radiation data that fail to pass the QA2 and QA3 are 0.77% and 0.49%, respectively. The method implemented by the Global Energy Balance Archive is also applied to check the data quality of solar radiation in China. Of the 84 stations with a time series longer that 20 yr, suspect data at 35 of the sites were found. Based on data that passed the QA tests, trends in ground solar radiation and the effect of the data quality assessment on the trends are analyzed. There is a decrease in ground solar global and direct radiation in China over the years under study. Although the quality assessment process has significant effects on the data from individual stations and/or time periods, it does not affect the long-term trends in the data.

We developed a new emission inventory for Asia (Regional Emission inventory in ASia (REAS) Version 1.1) for the period 1980–2020. REAS is the first inventory to integrate historical, present, and future emissions in Asia on the basis of a consistent methodology. We present here emissions in 2000, historical emissions for 1980–2003, and projected emissions for 2010 and 2020 of SO2, NOx, CO, NMVOC, black carbon (BC), and organic carbon (OC) from fuel combustion and industrial sources. Total energy consumption in Asia more than doubled between 1980 and 2003, causing a rapid growth in Asian emissions, by 28% for BC, 30% for OC, 64% for CO, 108% for NMVOC, 119% for SO2, and 176% for NOx. In particular, Chinese NOx emissions showed a marked increase of 280% over 1980 levels, and growth in emissions since 2000 has been extremely high. These increases in China were mainly caused by increases in coal combustion in the power plants and industrial sectors. NMVOC emissions also rapidly increased because of growth in the use of automobiles, solvents, and paints. By contrast, BC, OC, and CO emissions in China showed decreasing trends from 1996 to 2000 because of a reduction in the use of biofuels and coal in the domestic and industry sectors. However, since 2000, Chinese emissions of these species have begun to increase. Thus, the emissions of air pollutants in Asian countries (especially China) showed large temporal variations from 1980–2003. Future emissions in 2010 and 2020 in Asian countries were projected by emission scenarios and from emissions in 2000. For China, we developed three emission scenarios: PSC (policy success case), REF (reference case), and PFC (policy failure case). In the 2020 REF scenario, Asian total emissions of SO2, NOx, and NMVOC were projected to increase substantially by 22%, 44%, and 99%, respectively, over 2000 levels. The 2020 REF scenario showed a modest increase in CO (12%), a lesser increase in BC (1%), and a slight decrease in OC (−5%) compared with 2000 levels. However, it should be noted that Asian total emissions are strongly influenced by the emission scenarios for China.

A new gauge-based analysis of daily precipitation has been constructed on a 0.5° latitude–longitude grid over East Asia (5°–60°N, 65°–155°E) for a 26-yr period from 1978 to 2003 using gauge observations at over 2200 stations collected from several individual sources. First, analyzed fields of daily climatology are computed by interpolating station climatology defined as the summation of the first six harmonics of the 365-calendar-day time series of the mean daily values averaged over a 20-yr period from 1978 to 1997. These fields of daily climatology are then adjusted by the Parameter-Elevation Regressions on Independent Slopes Model (PRISM) monthly precipitation climatology to correct the bias caused by orographic effects. Gridded fields of the ratio of daily precipitation to the daily climatology are created by interpolating the corresponding station values using the optimal interpolation method. Analyses of total daily precipitation are finally calculated by multiplying the daily climatology by the daily ratio. Cross-validation tests indicated that this gauge-based analysis has high quantitative quality with a negligible bias and a correlation coefficient of ∼0.6 for comparisons between withdrawn station data and the analysis at a 0.05° latitude–longitude grid box. The quality of the analysis increases with the gauge network density. The mean distribution and annual cycle of this new gauge analysis present similar patterns but with more detailed structures and slightly larger magnitude compared to other published monthly gauge analyses over the region. The East Asia gauge analysis is applied to verify the performance of five satellite-based precipitation estimates. This examination reveals the regionally and seasonally dependent performance of the satellite products with the best statistics observed for relatively wet regions. Further improvements of the daily gauge analysis are underway to increase the gauge network density and to refine the algorithm to better deal with the orographic effects especially over South and Southeast Asia.

Land cover is classified over East Asia using 250-m Moderate Resolution Imaging Spectroradiometer (MODIS) land surface reflectance, MODIS snow cover and Operational Linescan System (OLS) human settlement data. The classification method includes a decision tree classification scheme that considers 11 kinds of land surface features derived from the OLS product and the time series of two MODIS products in 2000. The decision tree was defined manually based on the experiment because of insufficient training data, ease of tuning by visual interpretation, and extensibility to further research. The resulting classification is compared to three kinds of reference data, i.e. MODIS land cover product, Chinese digital land cover map, and Chinese census. The land cover classification can be input into a hydrological model applied to the Yellow River in China.