A method in near-surface estimation of air temperature (NEAT) in times following the satellite passing time using MODIS images

Air temperature is one of the most important parameters in environmental, agricultural and water resources studies. This information is not usually always available at the required temporal and spatial resolution. The air temperature is measured at a fixed point in the meteorological stations which are dispersed and may not have the appropriate spatial resolution needed for many applications. On the other hand, MODIS satellite images have relatively acceptable spatial resolution specially for use in environmental studies. There is a methodology with which the near surface air temperature can be extracted from MODIS images at the satellite passing time with an acceptable accuracy. The goal in this study is to find a way to predict the air temperature in times after/before the satellite passing time. The procedure consists of two steps. In the first step, the relationship between the air temperature at a time in a synoptic station and the air temperature in other times up to 5 h later were modeled. In the second step, using these built up relationships, the air temperature extracted from the satellite image at the passing time was extrapolated to the next hours. Finally, the results of this extrapolation method were evaluated using the air temperatures measured at those hours and in the pixels containing some other meteorological stations. The error of the method when applied to a relatively homogeneous surface cover was about 1.5 °C. This error when applied to the next hours, was below 2 °C up to 5 h after satellite passing time. This method can be useful in some agricultural and horticultural applications in which both the spatial and temporal resolution are needed simultaneously. This product is a useful tool for frost prediction, a phenomenon that usually happens at night or early in the morning.     

RIO: the R-process isotope observer

Our galaxy is filled with a “gas” of relativistic nuclei and electrons – the galactic cosmic rays (GCRs). The source of GCR nuclei is unknown, but there is a general consensus among high-energy astrophysicists that GCRs are accelerated by supernova (SN) shocks in the interstellar medium. The evidence in support of this picture is strong but indirect. However, the fact that the cosmic-ray spectrum extends continuously, without steps or peaks, to more than five orders of magnitude in energy beyond the limit of SN shock acceleration appears to be incompatible with this picture, at least without extreme fine-tuning of models. A “smoking gun” is needed to definitively establish that SN shocks are indeed the accelerator of GCRs. If GCRs are accelerated in SN shocks, they will be enhanced in freshly-synthesized r-process material. We are currently studying the R-process Isotope Observer (RIO) as a Mission of Opportunity for the International Space Station. RIO will make the first measurements of the isotopic abundances of the “ultraheavy” GCRs (those in the range 32 ⩽ Z ⩽ 42) and will determine the fractional contribution of freshly-synthesized r-process material in GCRs through the measurement of several key isotopic ratios.     

Modelling of air temperature using remote sensing and artificial neural network in Turkey

The aim of this research was to forecast monthly mean air temperature based on remote sensing and artificial neural network (ANN) data by using twenty cities over Turkey. ANN contained an input layer, hidden layer and an output layer. While city, month, altitude, latitude, longitude, monthly mean land surface temperatures were chosen as inputs, and monthly mean air temperature was chosen as output for network. Levenberg–Marquardt (LM) learning algorithms and tansig, logsig and linear transfer functions were used in the network. The data of Turkish State Meteorological Service (TSMS) and Technological Research Council of Turkey–Bilten for the period from 1995 to 2004 were chosen as training when the data of 2005 year were being used as test. Result of research was evaluated according to statistical rules. The best linear correlation coefficient (R), and root mean squared error (RMSE) between the estimated and measured values for monthly mean air temperature with ANN and remote sensing method were found to be 0.991–1.254 K, respectively.     

Space-radiation-induced photon luminescence of the Moon

We report on the results of a continuing study of the photon luminescence of the Moon induced by Galactic Cosmic Rays (GCRs) and space radiation from the Sun, using the Monte Carlo program FLUKA. Understanding the space radiation environment is critical to future exploration of the Moon, and this includes photons. The model of the lunar surface is taken to be the chemical composition of soils found at various landing sites during the Apollo and Luna programs, averaged over all such sites to define a generic regolith for the present analysis. This surface model then becomes the target that is bombarded by Galactic Cosmic Rays (GCRs) and Solar Energetic Particles (SEPs) or Solar Particle Events (SPEs) above 1 keV in FLUKA to determine the photon fluence albedo produced by the Moon’s surface when there is no sunlight and Earthshine. The result is to be distinguished from the gamma-ray spectrum produced by the radioactive decay of radiogenic constituents lying in the surface and interior of the Moon. From the photon fluence we derive the spectrum which can be utilized to examine existing lunar spectral data and to aid future orbiting instrumentation in the measurement of various components of the space-radiation-induced photon luminescence present on the Moon.     

Sunspot numbers,interplanetary magnetic field,and cosmic ray intensity at earth: Nexus for the twentieth century

The pivotal role played by the interplanetary magnetic field (B) in modulating galactic cosmic ray (GCR) intensity in the heliosphere is described. We show that the inverse correlation observed by Forbush (1958) between GCRs and sunspot numbers (SSNs) is reflected in high correlation between SSNs and B (cc = 0.94). The SSN data are available since 1700 and the derived B data since 1835. The paleo-cosmic ray data are available for several millennia in the form of ¹⁰Be radionuclide sequestered in polar ice. The data of the ion chambers (ICs) at the Cheltenham–Fredericksburg–Yakutsk (CFY) sites are combined to create a data string for 1937–1988. In turn, these data are used to extend the measurements of the low energy GCR ions (>0.1 GeV) at balloon altitudes at high latitudes in Russia to 1937. These data are then correlated to B and the fit parameters are used to extend the low energy ion data to 1900, creating the instrumental era GCR time series for the twentieth century. The derived GCR time series is compared to ¹⁰Be measured at two sites in Greenland, namely Dye 3 and NGRIP for 1900–2000 to check the internal consistency of datasets for the long-term trend. We find that the annual mean rate (%) for 1965 at NGRIP is an outlier. We replace it with the mean of 1964 and 1965 rates and construct a new re-normalized time series at NGIP, improving the agreement with the derived instrumental era GCR time series for the twentieth century as well. This should encourage its use by heliophysics community for varied applications.     

Impact of local and global factors and meteorological parameters in temporal variation of atmospheric potential gradient

In this research work, we have performed comparative diurnal variations of atmospheric Potential Gradient (PG) of fair-weather days by using the data of three stations installed in Northern, Pakistan for the year 2018. We investigated the impact of both local and global factors and meteorological parameters in the diurnal variation of atmospheric Potential Gradient on the annual and seasonal time scale. We observed two peaks, primary and secondary. This is because of the land-based measurements of annual and seasonal variations. The annual average curve of Potential Gradient of all three stations: Islamabad (CES), Muzaffarabad (MZF), and Balakot (BKT) demonstrated a notable deviation from the standard oceanic Carnegie curve. The atmospheric Potential Gradient variations are due to numerous meteorological factors e.g., air pollution, humidity, aerosol particles, fog, and temperature. Among three stations, the MZF station is located in highland (mountainous) and it demonstrated a higher atmospheric Potential Gradient. We further differentiate the results of our three stations with global results for authenticity and observed coherence between them. In addition, a positive correlation of fair-weather Potential Gradient is observed with temperature and a notable correlation between relative humidity and atmospheric Potential Gradient for all the three observatories.     

Surface temperature estimation in Singhbhum Shear Zone of India using Landsat-7 ETM+ thermal infrared data

Land surface temperature (LST) is an important factor in global change studies, heat balance and as control for climate change. A comparative study of LST over parts of the Singhbhum Shear Zone in India was undertaken using various emissivity and temperature retrieval algorithms applied on visible and near infrared (VNIR), and thermal infrared (TIR) bands of high resolution Landsat-7 ETM+ imagery. LST results obtained from satellite data of October 26, 2001 and November 2, 2001 through various algorithms were validated with ground measurements collected during satellite overpass. In addition, LST products of MODIS and ASTER were compared with Landsat-7 ETM+ and ground truth data to explore the possibility of using multi-sensor approach in LST monitoring. An image-based dark object subtraction (DOS3) algorithm, which is yet to be tested for LST retrieval, was applied on VNIR bands to obtain atmospheric corrected surface reflectance images. Normalized difference vegetation index (NDVI) was estimated from VNIR reflectance image. Various surface emissivity retrieval algorithms based on NDVI and vegetation proportion were applied to ascertain emissivities of the various land cover categories in the study area in the spectral range of 10.4–12.5 μm. A minimum emissivity value of about 0.95 was observed over the reflective rock body with a maximum of about 0.99 over dense forest. A strong correlation was established between Landsat ETM+ reflectance band 3 and emissivity. Single channel based algorithms were adopted for surface radiance and brightness temperature. Finally, emissivity correction was applied on ‘brightness temperature’ to obtain LST. Estimated LST values obtained from various algorithms were compared with field ground measurements for different land cover categories. LST values obtained after using Valor’s emissivity and single channel equations were best correlated with ground truth temperature. Minimum LST is observed over dense forest as about 26 °C and maximum LST is observed over rock body of about 38 °C. The estimated LST showed that rock bodies, bare soils and built-up areas exhibit higher surface temperatures, while water bodies, agricultural croplands and dense vegetations have lower surface temperatures during the daytime. The accuracy of the estimated LST was within ±2 °C. LST comparison of ASTER and MODIS with Landsat has a maximum difference of 2 °C. Strong correlation was found between LST and spectral radiance of band 6 of Landsat-7 ETM+. Result corroborates the fact that surface temperatures over land use/land cover types are greatly influenced by the amount of vegetation present.     

基于ACE飞船观测的银河宇宙线与太阳风变化的统计研究

基于ACE飞船的资料，通过时序迭加方法统计分析了最近两个太阳活动极小年时期（2007.0-2009.0和2016.5-2019.0年）的宇宙线计数与太阳风参数的关系.结果表明，宇宙线的计数受太阳风共转流相互作用区的强烈影响，宇宙线计数变化与快慢太阳风流界面的位置密切相关，例如流界面的穿越通常伴随着宇宙线计数的下降.分析表明，第一时段的具有“雪犁”效应的宇宙线计数下降对应于流界面附近的扩散系数急剧下降，而第二时段的非“雪犁”效应的计数下降可能是由穿越流界面后的扩散系数增大引起的.日球层电流片也与宇宙线计数变化存在一定的相关性，宇宙线粒子在日球层电流片附近存在一定程度的堆积.太阳风对宇宙线的作用机制表明，宇宙线的漂移和扩散效应决定了其在1AU附近的分布变化.      

Deriving a sea surface temperature record suitable for climate change research from the along-track scanning radiometers

We describe the approach to be adopted for a major new initiative to derive a homogeneous record of sea surface temperature for 1991–2007 from the observations of the series of three along-track scanning radiometers (ATSRs). This initiative is called (A)RC: (Advanced) ATSR Re-analysis for Climate. The main objectives are to reduce regional biases in retrieved sea surface temperature (SST) to less than 0.1 K for all global oceans, while creating a very homogenous record that is stable in time to within 0.05 K decade⁻¹, with maximum independence of the record from existing analyses of SST used in climate change research. If these stringent targets are achieved, this record will enable significantly improved estimates of surface temperature trends and variability of sufficient quality to advance questions of climate change attribution, climate sensitivity and historical reconstruction of surface temperature changes. The approach includes development of new, consistent estimators for SST for each of the ATSRs, and detailed analysis of overlap periods. Novel aspects of the approach include generation of multiple versions of the record using alternative channel sets and cloud detection techniques, to assess for the first time the effect of such choices. There will be extensive effort in quality control, validation and analysis of the impact on climate SST data sets. Evidence for the plausibility of the 0.1 K target for systematic error is reviewed, as is the need for alternative cloud screening methods in this context.     

Delineation of possible influence of solar variability and galactic cosmic rays on terrestrial climate parameters

The present paper has investigated the associations of solar activity (SA), represented by total solar irradiance (TSI), galactic cosmic rays (GCR) and terrestrial climate parameters in particular the global cloudiness and global surface temperature. To that end, we have analysed thirty five years (1983–2018) data of these parameters and have applied the Granger-causality test in order to assess whether there is any potential predictability power of one indicator to the other. The correlations among the involved parameters are tested using Vector Auto Regression (VAR) model and variance decomposition method. As a result of the above analysis, we have found that the TSI is an important factor and has contributed about 8.77 ± 0.42% in the cosmic ray intensity variations. In case of cloud cover variations, the other three parameters (TSI, cosmic ray and global surface temperature) have played a significant role. Further, the TSI changes have contributed 1.68 ± 0.03% fluctuations in the variance of the cloud cover while the cosmic ray intensity and global surface temperature have contributed about 4.89 ± 0.08% and 10.87 ± 1.41% respectively. In case of the global surface temperature anomaly both TSI and cloud covers have contributed about 5.07 ± 0.47% and 14.42 ± 2.13% fluctuations respectively. Additionally, we have also assessed the impact of internal climate oscillations like multivariate ENSO index (MEI), north Atlantic oscillations (NAO) and quasi biennial oscillations (QBO) on cloud cover variations. The contribution of these internal oscillations e.g. ENSO, NAO and QBO in cloud cover variation were reported as 7.48 ± 1.02%, 5.51 ± 0.16% and 1.36 ± 0.43% respectively.     

The accuracy of SST retrievals from AATSR: An initial assessment through geophysical validation against in situ radiometers,buoys and other SST data sets

The Advanced Along-Track Scanning Radiometer (AATSR) was launched on Envisat in March 2002. The AATSR instrument is designed to retrieve precise and accurate global sea surface temperature (SST) that, combined with the large data set collected from its predecessors, ATSR and ATSR-2, will provide a long term record of SST data that is greater than 15 years. This record can be used for independent monitoring and detection of climate change. The AATSR validation programme has successfully completed its initial phase. The programme involves validation of the AATSR derived SST values using in situ radiometers, in situ buoys and global SST fields from other data sets. The results of the initial programme presented here will demonstrate that the AATSR instrument is currently close to meeting its scientific objectives of determining global SST to an accuracy of 0.3 K (one sigma). For night time data, the analysis gives a warm bias of between +0.04 K (0.28 K) for buoys to +0.06 K (0.20 K) for radiometers, with slightly higher errors observed for day time data, showing warm biases of between +0.02 (0.39 K) for buoys to +0.11 K (0.33 K) for radiometers. They show that the ATSR series of instruments continues to be the world leader in delivering accurate space-based observations of SST, which is a key climate parameter.     

Effect of the troposphere on surface neutron counter measurements

Surface neutron counter data are often used as a proxy for atmospheric ionisation from cosmic rays in studies of extraterrestrial effects on climate. Neutron counter instrumentation was developed in the 1950s and relationships between neutron counts, ionisation and meteorological conditions were investigated thoroughly using the techniques available at the time; the analysis can now be extended using modern data. Whilst surface neutron counts are shown to be a good proxy for ionisation rate, the usual meteorological correction applied to surface neutron measurements, using surface atmospheric pressure, does not completely compensate for tropospheric effects on neutron data. Residual correlations remain between neutron counts, atmospheric pressure and geopotential height, obtained from meteorological reanalysis data. These correlations may be caused by variations in the height and temperature of the atmospheric layer at ∼100 hPa. This is where the primary cosmic rays interact with atmospheric air, producing a cascade of secondary ionising particles.     

Estimation of Galactic Cosmic Ray exposure inside and outside the Earth’s magnetosphere during the recent solar minimum between solar cycles 23 and 24

The evidently low solar activity observed between solar cycles 23 and 24 during the years 2008–2010 led to a substantial increase in the Galactic Cosmic Ray (GCR) intensity in comparison with preceding solar minima. As the GCRs consist of highly-ionizing charged particles having the potential to cause biological damage, they are a subject of concern for manned missions to space. With the enhanced particle fluxes observed between 2008 and 2010, it is reasonable to assume that the radiation exposure from GCR must have also increased to unusually high levels. In this paper, the GCR exposure outside and inside the Earth’s magnetosphere is numerically calculated for time periods starting from 1970 to the end of 2011 in order to investigate the increase in dose levels during the years 2008–2010 in comparison with the last three solar minima. The dose rates were calculated in a water sphere, used as a surrogate for the human body, either unshielded or surrounded by aluminium shielding of 0.3, 10 or 40 g/cm².     

Modelling of galactic Carbon in an asymmetrical heliosphere: Effects of asymmetrical modulation conditions

Observations of galactic cosmic rays (GCRs) from the two Voyager spacecraft inside the heliosheath indicate significant differences between them, suggesting that in addition to a possible global asymmetry in the north–south dimensions (meridional plane) of the heliosphere, it is also possible that different modulation (turbulence) conditions could exist between the two hemispheres of the heliosphere. We focus on illustrating the effects on GCR Carbon of asymmetrical modulation conditions combined with a heliosheath thickness that has a significant dependence on heliolatitude. To reflect different modulation conditions between the two heliospheric hemispheres in our numerical model, the enhancement of both polar and radial perpendicular diffusion off the ecliptic plane is assumed to differ from heliographic pole to pole. The computed radial GCR intensities at polar angles of 55° (approximating the Voyager 1 direction) and 125° (approximating the Voyager 2 direction) are compared at different energies and for both particle drift cycles. This is done in the context of illustrating how different values of the enhancement of both polar and radial perpendicular diffusion between the two hemispheres contribute to causing differences in radial intensities during solar minimum and moderate maximum conditions. We find that in the A > 0 cycle these differences between 55° and 125° change both quantitatively and qualitatively for the assumed asymmetrical modulation condition as reflected by polar diffusion, while in the A < 0 cycle, minute quantitative differences are obtained. However, when both polar and radial perpendicular diffusion have significant latitude dependences, major differences in radial intensities between the two polar angles are obtained in both polarity cycles. Furthermore, significant differences in radial intensity gradients obtained in the heliosheath at lower energies may suggest that the solar wind turbulence at and beyond the solar wind termination shock must have a larger latitudinal dependence.     

Influence of land surface parameters on the spatio-seasonal land surface temperature regime in rural West Bengal,India

The magnitude and causes of changes in the land surface temperature of rural areas have not been extensively studied. The thermal band of Landsat imagery is taken to extract winter, summer, and monsoon season land surface temperature (LST) and relate it to surface parameters over a 30-year period. From the extracted parameters constructed a prospective surface temperature (PST) model using Multivariate Adaptive Regression Splines. The Chandrabhaga river basin in West Bengal of the lateritic Rarh Tract at the Chota Nagpur Plateau fringe was chosen as the study area because it is far from urban influences, to avoid the well-known heat island effect. Over the study period, summer and winter average LST increased linearly by 0.085?°C/y and 0.016?°C/y respectively. These results were validated with air temperature (RMSE?=?x and y, respectively). Over time more of the area is in the higher temperature zones, e.g., in April 2011, 4% area exceeded >32°, whereas in 2015 this proportion reached 52%. PST models of all the seasons were moderate to highly correlate (0.57–0.87) with actual LST, showing the value of this model. It also revealed the relative importance of the regional factors. Based on this information factor management is a scientific step to restrict or minimize the temperature rise effect.     

Global MGS TES data and Mars-GRAM validation

Mars Global Reference Atmospheric Model (Mars-GRAM 2001) is an engineering-level Mars atmosphere model widely used for many Mars mission applications. From 0 to 80 km, it is based on NASA Ames Mars General Circulation Model (MGCM), while above 80 km it is based on University of Michigan Mars Thermospheric General Circulation Model. Mars-GRAM 2001 and MGCM use surface topography from Mars Global Surveyor Mars Orbiter Laser Altimeter (MOLA). Validation studies are described comparing Mars-GRAM with a global summary data set of Mars Global Surveyor Thermal Emission Spectrometer (TES) data. TES averages and standard deviations were assembled from binned TES data which covered surface to ∼40 km, over more than a full Mars year (February 1999–June 2001, just before start of a Mars global dust storm). TES data were binned in 10° × 10° latitude–longitude bins (36 longitude bins, centered at 5°–355°, by 18 latitude bins, centered at −85° to +85°), and 12 seasonal bins (based on 30° increments of L_s angle). Bin averages and standard deviations were assembled at 23 data levels (temperature at 21 pressure levels, plus surface temperature and surface pressure). Two time-of-day bins were used: local time near 2 or 14 h. Two dust optical depth bins were used: infrared optical depth, either less than or greater than 0.25 (which corresponds to visible optical depth less than or greater than about 0.5). For interests in aerocapture and precision entry and landing, comparisons focused on atmospheric density. TES densities versus height were computed from TES temperature versus pressure, using assumptions of perfect gas law and hydrostatics. Mars-GRAM validation studies used density ratio (TES/Mars-GRAM) evaluated at data bin center points in space and time. Observed average TES/Mars-GRAM density ratios were generally 1 ± 0.05, except at high altitudes (15–30 km, depending on season) and high latitudes (>45°N), or at most altitudes in the southern hemisphere at L_s ∼ 90° and 180°. Compared to TES averages for a given latitude and season, TES data had average density standard deviation about the mean of ∼2.5% for all data, or ∼1–4%, depending on time of day and dust optical depth. Average standard deviation of TES/Mars-GRAM density ratio was 8.9% for local time 2 h and 7.1% for local time 14 h. Thus standard deviation of observed TES/Mars-GRAM density ratio, evaluated at matching positions and times, is about three times the standard deviation of TES data about the TES mean value at a given position and season.     

Effect of solar activity on the repetitiveness of some meteorological phenomena

In this paper we research the relationship between solar activity and the weather on Earth. This research is based on the assumption that every ejection of magnetic field energy and particles from the Sun (also known as Solar wind) has direct effects on the Earth’s weather. The impact of coronal holes and active regions on cold air advection (cold fronts, precipitation, and temperature decrease on the surface and higher layers) in the Belgrade region (Serbia) was analyzed. Some active regions and coronal holes appear to be in a geo-effective position nearly every 27 days, which is the duration of a solar rotation. A similar period of repetitiveness (27–29 days) of the passage of the cold front, and maximum and minimum temperatures measured at surface and at levels of 850 and 500 hPa were detected. We found that 10–12 days after Solar wind velocity starts significantly increasing, we could expect the passage of a cold front. After eight days, the maximum temperatures in the Belgrade region are measured, and it was found that their minimum values appear after 12–16 days. The maximum amount of precipitation occurs 14 days after Solar wind is observed. A recurring period of nearly 27 days of different phases of development for hurricanes Katrina, Rita and Wilma was found. This analysis confirmed that the intervals of time between two occurrences of some particular meteorological parameter correlate well with Solar wind and A index.     

Ionospheric reflection of the magnetic activity described by the index η

Differences in the external part of the vertical geomagnetic component point to the existence of local inhomogeneities in the magnetosphere or the ionosphere. Usually used magnetic indices are not sufficient to express the state of ionosphere, the common used global Kp index derived in the three-hour interval does not indicate much more rapidly changes appearing in ionosphere. Magnetic index η reflects ionospheric disturbances when other indices show very quiet conditions. Data of ionospheric characteristics (foE, foEs, h’E, h’F2) during 28-day long quiet day conditions (Kp = 0–2) in 2004 were analyzed. The correlations between strong local disturbances in ionosphere during very quiet days and high values of magnetic index η were found. The most sensitive to magnetic influence – ionospheric E layer data (foE characteristic) – reaches median deviations up to (+0.8 MHz and −0.8 MHz) during very low magnetic activity (Kp = 0–1). The high peaks (2–2.7) of the magnetic index η correlate in time with large local median deviations of foE. Such local deviations can suggest local inhomogeneities (vertical drifts) in the ionosphere. The correlation in space is not trivial. The strong peak of η is situated between the positive and negative deviations of foE. Additional observation is connected with correlation in time of the high η value with the negative median deviations of h’F2 (in some cases up to −90 km). The analysis was based on one-minute data recorded at each of 20 European Magnetic Observatories working in the INTERMAGNET network and from 19 ionosondes for 2004. Ionospheric data are sparse in time and in space in opposite to the magnetic data. The map of the magnetic indices can suggest the behavior of ionospheric characteristics in the areas where we have no data.     

Monitoring spatio-temporal variations in aerosols and aerosol–cloud interactions over Pakistan using MODIS data

Clouds are important elements in climatic processes and interactions between aerosols and clouds are therefore a hot topic for scientific research. Aerosols show both spatial and temporal variations, which can lead to variations in the microphysics of clouds. In this research, we have examined the spatial and temporal variations in aerosol particles over Pakistan and the impact of these variations on various optical properties of clouds, using Moderate Resolution Imaging Spectroradiometer (MODIS) data from the Terra satellite. We used the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model for trajectory analysis to reveal the origins of air masses, with the aim of understanding these spatial and temporal variabilities in aerosol concentrations. We also documented seasonal variations in patterns of aerosol optical depth (AOD) over Pakistan, for which the highest values occur during the monsoon season (June–August). We then analyzed the relationships between AOD and four other cloud parameters, namely water vapour (WV), cloud fraction (CF), cloud top temperature (CTT) and cloud top pressure (CTP). Regional correlation maps and time series plots for aerosol (AOD) and cloud parameters were produced to provide a better understanding of aerosol–cloud interaction. The analyses showed strong positive correlations between AOD and WV for all of the eight cities investigated. The correlation between AOD and CF was positive for those cities where the air masses were predominantly humid, but negative for those cities where the air masses were relatively dry and carried a low aerosol abundance. These correlations were clearly dependent on the meteorological conditions for all of the eight cities investigated. Because of the observed AOD–CF relationship, the co-variation of AOD with CTP and CTT may be attributable to large-scale meteorological variations: AOD showed a positive correlation with CTP and CTT in northern regions of Pakistan and a negative correlation in southern regions.     

Simulation of the land surface temperature from moon-based Earth observations

The land surface temperature (LST) is a key parameter for the Earth’s energy balance. As a natural satellite of the Earth, the orbital of the moon differs from that of current Earth observation satellites. It is a new way to measure the land surface temperature from the moon and has many advantages compared with artificial satellites. In this paper, we present a new method for simulating the LST measured by moon-based Earth observations. Firstly, a modified land-surface diurnal temperature cycle (DTC) method is applied to obtain the global LST at the same coordinated universal time (UTC) using the Moderate Resolution Imaging Spectroradiometer (MODIS) LST products. The lunar elevation angles calculated using the ephemeris data (DE405) from the Jet Propulsion Laboratory (JPL) were then applied to simulate the Earth coverage observed from the moon. At the same time, the modified DTC model was validated using in situ data, MODIS LST products, and the FengYun-2F (FY-2F) LST, respectively. The results show that the fitting accuracy (root-mean-square error, RMSE) of the modified DTC model is not greater than 0.72?°C for eight in situ stations with different land cover types, and the maximum fitting RMSE of the modified model is smaller than that of current DTC models. By the comparison of the simulated LST with MODIS and FY-2F LST products, the errors of the results were feasible and accredited, and the simulated global LST has a reasonable spatiotemporal distribution and change trend. The simulated LST data can therefore be used as base datasets to simulate the thermal infrared imagery from moon-based Earth observations in future research.