Moderate Surface Temperature Research Articles

Impacts of Urban Morphology on Seasonal Land Surface Temperatures: Comparing Grid- and Block-Based Approaches

Climate change is expected to result in increased occurrences of extreme weather events such as heat waves and cold spells. Urban planning responses are crucial for improving the capacity of cities and communities to deal with significant temperature variations across seasons. This study aims to investigate the relationship between urban temperature fluctuations and urban morphology throughout the four seasons. Through quadrant and statistical analyses, built-environment factors are identified that moderate or exacerbate seasonal land surface temperatures (LSTs). The focus is on Seoul, South Korea, as a case study, and seasonal LST values are calculated at both the grid (100 m × 100 m) and street block levels, incorporating factors such as vegetation density, land use patterns, albedo, two- and three-dimensional building forms, and gravity indices for large forests and water bodies. The quadrant analysis reveals a spatial segregation between areas demonstrating high LST adaptability (cooler summers and warmer winters) and those displaying LST vulnerability (hotter summers and colder winters), with significant differences in vegetation and building forms. Spatial regression analyses demonstrate that higher vegetation density and proximity to water bodies play key roles in moderating LSTs, leading to cooler summers and warmer winters. Building characteristics have a constant impact on LSTs across all seasons: horizontal expansion increases the LST, while vertical expansion reduces the LST. These findings are consistent for both grid- and block-level analyses. This study emphasizes the flexible role of the natural environment in moderating temperatures.

Identification of geothermal potential based on land surface temperature derived from remotely sensed data.

With the continuous development of thermal infrared remote sensing technology and the maturation of remote sensing inversion algorithms based on surface temperatures, identifying high-temperature anomalous areas by inverting surface temperatures has become an crucial approach to finding geothermal potential areas. The eastern region of Longyang in western Yunnan Province is renowned for geothermal resources, though the distribution area of geothermal potential remains unknown. Therefore, this study used Landsat-8 TIRS data and four surface temperature inversion algorithms, namely, mono-window algorithm, single-channel algorithm, Du split window algorithm (SWD), and Jiménez-Muñoz split window algorithm (SWJ), to explore the astern region of Longyang. The inversion results were compared with Moderate Resolution Imaging Spectroradiometer Land Surface Temperature (MODIS LST) results for analysis and cross-validation to select the optimal algorithm. A multi-view remote sensing temperature anomaly information extraction method was adopted. Moreover, the overall threshold method, the fracture structure buffer method, and the joint analysis of diurnal temporal data were combined for the reduction of the thermal anomaly area as well as for comprehensively defining the geothermal prospective area in the study area. The results demonstrated that the mono-window algorithm had the highest accuracy with a Pearson coefficient of 0.77, which is more suitable for the surface temperature inversion in Longyang area. Furthermore, three geothermal anomalies (A, B, and C) were identified in the study area, with larger thermal anomaly in A and C, but a smaller one in B. All three areas had hot spring points verified, with A and C exhibiting more significant development potential. The research results provide a reliable methodological basis for the development of geothermal resources in the region.

Assessment of forest fire emissions in Uttarakhand State, India, using Open Geospatial data and Google Earth Engine.

In the recent past, forest fires have increased due to the changing climate pattern. It is necessary to analyse and quantify various gaseous emissions so as to mitigate their harmful effects on air pollution. Satellite remote sensing data provides an opportunity to study the greenhouse gases in the atmosphere. The multispectral sensor of the Tropospheric Monitoring Instrument (Sentinel-5) is capable of recording the reflectance of wavelengths vital for measuring the atmospheric concentrations of methane, formaldehyde, aerosol, carbon monoxide, etc., at a spatial resolution of 0.01°. The present study utilized the Google Earth Engine (GEE) platform to study the emissions caused by forest fires in four districts of Uttarakhand State of India, which witnessed unprecedented fires in April-May 2021. All the datasets were ingested in GEE, which has the capability to analyse large datasets without the need to download them. The pre-fire period chosen was September 2020; the fire period was February-May 2021, and the post-fire period was June 2021. The variables chosen were aerosol absorbing index (AAI), carbon monoxide (CO) and nitrogen dioxide (NO2). The climate parameter temperature (Moderate Resolution Imaging Spectroradiometer Land Surface Temperature) and precipitation (from Climate Hazards Group InfraRed Precipitation (CHIRPS) Pentad) were also studied for the period mentioned. The results indicate a different trend for emissions in each district. For AAI, maximum emissions were noted in district Nainital followed by Almora, Tehri Garhwal and Garhwal. For CO emissions, the most affected district was Almora followed by Nainital, Garhwal and Tehri Garhwal. For NO2 emissions, the most affected district was Garhwal, followed by Nainital, Tehri Garhwal and Almora. Delta Normalized Burn Ratio was computed from Sentinel data (difference of pre-fire and post-fire images) to assess the burnt area severity. The Delta Normalized Burn Ratio values observed that the district with the most burnt area is Garhwal, followed by Nainital, Almora and Tehri Garhwal. The elevated temperatures and scanty rainfall patterns regulated the intensity and duration of forest fire. Monitoring the gaseous emissions as a consequence of forest fire in the GEE platform is much easier and more convenient at a regional level. Such data is much needed for mitigation measures to be implemented in time.

Spatiotemporal Evolution and Hysteresis Analysis of Drought Based on Rainfed-Irrigated Arable Land

Drought poses a serious threat to agricultural production and food security in the context of global climate change. Few studies have explored the response mechanism and lag time of agricultural drought to meteorological drought from the perspective of cultivated land types. This paper analyzes the spatiotemporal evolution patterns and hysteresis relationship of meteorological and agricultural droughts in the middle and lower reaches of the Yangtze River in China. Here, the Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index products and surface temperature products were selected to calculate the Temperature Vegetation Dryness Index (TVDI) from 2010 to 2015. Furthermore, we obtained the Standardized Precipitation Evapotranspiration Index (SPEI) and the Palmer Drought Severity Index (PDSI) for the same period. Based on these indices, we analyzed the correlation and the hysteresis relationship between agricultural and meteorological drought in rainfed and irrigated arable land. The results showed that, (1) compared with SPEI, the high spatial resolution PDSI data were deemed more suitable for the subsequent accurate and scientific analysis of the relationship between meteorological and agricultural droughts. (2) When meteorological drought occurs, irrigated arable land is the first to experience agricultural drought, and then alleviates when the drought is most severe in rainfed arable land, indicating that irrigated arable land is more sensitive to drought events when exposed to the same degree of drought risk. However, rainfed arable land is actually more susceptible to agricultural drought due to the intervention of irrigation measures. (3) According to the cross-wavelet transform analysis, agricultural droughts significantly lag behind meteorological droughts by about 33 days during the development process of drought events. (4) The spatial distribution of the correlation coefficient between the PDSI and TVDI shows that the area with negative correlations of rainfed croplands and the area with positive correlations of irrigated croplands account for 77.55% and 68.04% of cropland areas, respectively. This study clarifies and distinguishes the details of the meteorological-to-agricultural drought relationship in rainfed and irrigated arable land, noting that an accurate lag time can provide useful guidance for drought monitoring management and irrigation project planning in the middle and lower reaches of the Yangtze River.

Evapotranspiration Over the Indian Region: Implications of Climate Change and Land Use/Land Cover Change

Evapotranspiration (ET) plays a significant role in climatic studies, directly influencing the hydrological cycle, energy balance equation, and surface vegetation. ET comprises three components: bare soil or ground evaporation, evaporation, and transpiration, in which vegetation removes water influenced by food grain production. In turn, soil moisture availability depends on precipitation characteristics over land, surface net radiation, and wind speed are the major climatic factors that together determine the magnitude of ET. This controls moisture availability in the lower troposphere, hence atmospheric stability, chances of cloud formation, and precipitation. Though the study of evapotranspiration is important for determining agricultural water consumption and analyzing drought situations, there is a lot of uncertainty in its accurate estimation. Land use/Land cover changes (LULCC) occurring throughout the Indian subcontinent have been found to affect the characteristics of low to moderate rainfall events and surface temperature extremes (Halder et al. 2016). A global warming scenario will change the hydrological cycle, and the impact of anthropogenic factors has also necessitated the need to understand the mechanisms that control changes in ET over India. In this study, we want to analyze the relationship between transpiration and the Normalized Difference Vegetation Index (NDVI) and investigate the relationship between canopy interception with respect to NDVI all over the Indian region. Attempts have been made to assess the impact of changes in climate and LULC on ET and its three components over the Indian region from 1981 till the present time. The monsoon season increases precipitation, and soil evaporation is found to increase at first, along with an increase in NDVI followed by canopy evaporation and transpiration. It is noted that changes in precipitation and LULCC across the Indian subcontinent have contributed significantly to changes in ET in different seasons. As variability in surface net radiation also plays an important role in controlling changes in total ET, it is being investigated.

Relationship between Crustal Deformation and Thermal Anomalies in the 2022 Ninglang Ms 5.5 Earthquake in China: Clues from InSAR and RST

On 2 January 2022, an earthquake of Ms 5.5 occurred in Ninglang County, Lijiang City, the earthquake-prone area of northwestern Yunnan. Whether this earthquake caused significant deformation and thermal anomalies and whether there is a relationship between them needs further investigation. Currently, multi-source remote sensing technology has become a powerful tool for long-time-series monitoring of earthquakes and active ruptures which mainly focuses on single crustal deformation and thermal anomaly. This study aims to reveal the crustal deformation and thermal anomaly characteristics of the Ninglang earthquake by using both Interferometric Synthetic Aperture Radar (InSAR) and Robust Satellite Techniques (RST). First, Sentinel-1A satellite SAR data were selected to obtain the coseismic deformation field based on Differential InSAR (D-InSAR), and the Small Baseline Set InSAR (SBAS-InSAR) technique was exploited to invert the pre- and post-earthquake displacement sequences. Then, RST was used to extract the thermal anomalies before and after the earthquake by using Moderate Resolution Imaging Spectroradiometer Land Surface Temperature (MODIS LST). The results indicate that the seismic crustal deformation is dominated by subsidence, with 23 thermal anomalies before and after the earthquake. It is speculated that the Yongning Fault in the deformation area is the main seismogenic fault of the Ninglang earthquake, which is dominated by positive fault dip-slip motion. Meanwhile, the seismic fault system composed of NE- and NW-oriented faults is an important factor in the formation of thermal anomalies, which are accompanied by changes in stress at different stages before and after the earthquake. Moreover, the crustal deformation and seismic thermal anomalies are correlated in time and space, and the active rupture activities in the region produce deformation accompanied by changes in thermal radiation. This study provides clues from remote sensing observations for analyzing the Ninglang earthquake and provides a reference for the joint application of InSAR and RST for earthquake monitoring.

Numerical investigation of regimes of current transfer to anodes of high-pressure arc discharges

Unified 1D numerical modeling of high-pressure high-current arc discharges is revisited. Two regimes of current transfer to anodes are investigated. The “passive anode” regime occurs for low and moderate anode surface temperatures Ta. The energy flux from the plasma to the anode surface, qpl, depends on Ta rather weakly in this regime and may be conveniently expressed in terms of the local current density jc, and the so-called anode heating voltage Uh. Uh is independent of the arc length and the cathode surface temperature, although it weakly varies with jc between approximately 6 and 8.5 V for jc in the range from 105 to 108 A m−2. In the “active anode” regime, qpl is higher than in the passive anode regime and varies with Ta. The active anode regime may occur on hot refractory anodes, such as those of high-intensity discharge lamps, when Ta exceeds approximately 3000 K and the thermionic electron emission from the anode comes into play. The latter causes an increase in the electron density near the anode. One consequence is the increase in the electron energy transport from the bulk plasma to the near-anode layer by electron heat conduction. The other effect contributing to increase in qpl is the formation of a negative near-anode space-charge sheath with a positive voltage drop. In non-stationary simulations, the active regime occurs via the development of a thermal instability similar to that causing the appearance of spots on thermionic arc cathodes. The occurrence of the active regime is strongly affected by parameters, in particular, by the distance between the anode surface and the cooling fluid.

Thermal damage and fatigue estimation in heavily loaded lubricated rolling/sliding contacts with Micro-Geometry

A previously developed model for heavily loaded Elastohydrodynamically lubricated (EHL) contacts with surface micro-geometry for the calculation of surface distress (micropitting), based on high-cycle fatigue and mild wear competition, is herewith further extended. It now includes the effects of frictional heating with a sharp temperature rise developed in the rolling contact. For this, a new surface damage model, originated in creep modelling, is included. With this modification, the detrimental effect of high temperature developed in the rolling/sliding contact can now be accounted for. This model can consider sharp or moderate surface temperature rise during over-rolling is found in bearings and gears operating at high speeds or under the combination of speeds, loads and unfavourable environmental aspects. The present model introduces a threshold limit made of the combination of temperature and (heating time under stress) load cycles above which the conditions in the rolling contact are deemed damaging for the steel microstructure and the tribological functionality of the rolling contact. The surface damage model is first compared with laboratory experiments in rolling/sliding conditions and then applied to study combinations of loads, sliding speeds and the effect in rolling bearings. The ability of the present model to include damaging mechanisms, other than classical metal fatigue, increases the flexibility in contact surface damage modelling and allows for the accounting of phenomena up to now excluded from better estimation of the machine elements surface life.

Explosive bouncing on heated silicon surfaces under low ambient pressure.

Droplet impingement on heated surfaces has been investigated by varying the surface textures, temperature, and droplet properties with demonstration of various phenomenological behaviors, such as evaporation, boiling, splashing, and Leidenfrost bouncing. However, the ambient pressure dependence has not been well explored, especially for ambient pressures lower than 5 kPa. By examining the ambient pressure (from 0.2 to 20 kPa) and surface temperature (from 20 to 200 °C) simultaneously, we found a novel explosive bouncing behavior which is different from Leidenfrost bouncing and only occurs at extremely low ambient pressure (≤6 kPa). Through experimental validation and mechanical analysis, we found that the explosive bouncing is caused by the dramatic explosion of the local vapor bubble and reducing the ambient pressure benefits the formation and explosion of the vapor bubble.

Quantum surface diffusion in Bohmian mechanics

Surface diffusion of small adsorbates is analyzed in terms of the so-called intermediate scattering function and dynamic structure factor, observables in experiments using the well-known quasielastic Helium atom scattering and Helium spin echo techniques. The linear theory applied is an extension of the neutron scattering due to van Hove and considers the time evolution of the position of the adsorbates in the surface. This approach allows us to use a stochastic trajectory description following the classical, quantum and Bohmian frameworks. Three different regimes of motion are clearly identified in the diffusion process: ballistic, Brownian and intermediate which are well characterized, for the first two regimes, through the mean square displacements and Einstein relation for the diffusion constant. The Langevin formalism is used by considering Ohmic friction, moderate surface temperatures and small coverages. In the Bohmian framework, analyzed here, the starting point is the so-called Schrödinger-Langevin equation which is a nonlinear, logarithmic differential equation. By assuming a Gaussian function for the probability density, the corresponding quantum stochastic trajectories are given by a dressing scheme consisting of a classical stochastic trajectory followed by the center of the Gaussian wave packet, and issued from solving the Langevin equation (particle property), plus the time evolution of its width governed by the damped Pinney differential equation (wave property). The Bohmian velocity autocorrelation function is the same as the classical one when the initial spread rate is assumed to be zero. If not, in the diffusion regime, the Brownian-Bohmian motion shows a weak anomalous diffusion.

K2-155: A Bright Metal-poor M Dwarf with Three Transiting Super-Earths

Abstract We report on the discovery of three transiting super-Earths around K2-155 (EPIC 210897587), a relatively bright early M dwarf (V = 12.81 mag) observed during Campaign 13 of the NASA K2 mission. To characterize the system and validate the planet candidates, we conducted speckle imaging and high-dispersion optical spectroscopy, including radial velocity measurements. Based on the K2 light curve and the spectroscopic characterization of the host star, the planet sizes and orbital periods are and 6.34365 ± 0.00028 days for the inner planet; and 13.85402 ± 0.00088 days for the middle planet; and and 40.6835 ± 0.0031 days for the outer planet. The outer planet (K2-155d) is near the habitable zone, with an insolation 1.67 ± 0.38 times that of the Earth. The planet’s radius falls within the range between that of smaller rocky planets and larger gas-rich planets. To assess the habitability of this planet, we present a series of three-dimensional global climate simulations, assuming that K2-155d is tidally locked and has an Earth-like composition and atmosphere. We find that the planet can maintain a moderate surface temperature if the insolation proves to be smaller than ∼1.5 times that of the Earth. Doppler mass measurements, transit spectroscopy, and other follow-up observations should be rewarding, as K2-155 is one of the optically brightest M dwarfs known to harbor transiting planets.

Detection of haze and its intensity based on visibility and relative humidity estimated from MODIS data

ABSTRACTOver recent years, air pollution has become a serious environmental problem with frequent occurrence of hazy days in many Chinese cities. In this study, a satellite-based method was developed to detect haze and its intensity for the Chinese city of Nanjing. This detection was based on the joint consideration of two indices, visibility, and relative humidity. They were determined from the Moderate Resolution Imaging Spectroradiometer-derived aerosol optical thickness, surface temperature, and precipitable water vapour data. Evaluated against the in situ measured results, haze and its intensity were found to be detected at a maximum accuracy of 81.7% and 60%, respectively. Of the two indices, visibility plays a more important role than relative humidity in affecting the detection accuracy. It is concluded that it is feasible to detect haze and its intensity from satellite data.

Multiphonon excitation and quantum decoherence in neon scattering from solid surfaces

We present angle- and energy-resolved analysis of Ne scattering from a Ni(111) surface at moderate beam energy and surface temperature. Variation of the surface temperature allows the transition from a pure quantum regime, where single-phonon events are observed, to the classical regime, where multiphonon excitations are observed. The latter can be reproduced by classical calculations. Therefore, our data lie on the border between the coherent quantum regime and the incoherent classical regime.

Quantifying evaporation and its decadal change for Lake Nam Co, central Tibetan Plateau

AbstractMost lakes in the interior Tibetan Plateau have expanded rapidly since the late 1990s. Because of a lack of observations, lake water balances and their changes are far from well understood. Evaporation is a component of the lake water balance, and this study quantifies its magnitude, decadal change, and its contribution to the water balance changes in Lake Nam Co, one of the largest lakes on the Tibetan Plateau (with an area of approximately 2000 km2 and a mean depth of approximately 40 m). The lake temperature and the evaporation are simulated by the Flake model. The simulation results are validated against observed lake temperature profile from 2013 and Moderate Resolution Imaging Spectroradiometer lake surface temperature data from 2000 to 2014. The simulated latent heat flux and sensible heat flux are validated against Bowen ratio‐derived estimates for 2013. Based on the validated simulation results, the long‐term mean annual evaporation is approximately 832 ± 69 mm, and this value is much less than the potential evaporation estimated using the Penman‐Monteith equation. The annual evaporation from 1980 to 2014 displays a complex decadal oscillation, mainly due to the changes in energy‐related terms (air temperature and radiation). The mean lake evaporation since the late 1990s is greater than previous periods; thus, this change in evaporation has suppressed the recent expansion of Nam Co.

Condensation corrosion of carbon steel at low to moderate surface temperature and iron carbonate precipitation kinetics

This study investigates the influence of surface temperature and droplet retention time (DRT) on the corrosion rate, FeCO3 supersaturation, and scaling tendency of carbon steel exposed to water condensation. This corrosion phenomenon is also known as top of the line corrosion (TLC). TLC is found to be governed by surface temperature irrespective of water condensation rates (WCR) at low surface temperature (15°C). The results also demonstrate that the DRT directly influences FeCO3 supersaturation and scale formation. A new kinetic constant for the calculation of FeCO3 precipitation rate under condensing condition at the top of the line is proposed.

Uncertainties of satellite-derived surface skin temperatures in the polar oceans: MODIS, AIRS/AMSU, and AIRS only

Abstract. Uncertainties in the satellite-derived surface skin temperature (SST) data in the polar oceans during two periods (16–24 April and 15–23 September) 2003–2014 were investigated and the three data sets were intercompared as follows: MODerate Resolution Imaging Spectroradiometer Ice Surface Temperature (MODIS IST), the SST of the Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit-A (AIRS/AMSU), and AIRS only. The AIRS only algorithm was developed in preparation for the degradation of the AMSU-A. MODIS IST was systematically warmer up to 1.65 K at the sea ice boundary and colder down to −2.04 K in the polar sea ice regions of both the Arctic and Antarctic than that of the AIRS/AMSU. This difference in the results could have been caused by the surface classification method. The spatial correlation coefficient of the AIRS only to the AIRS/AMSU (0.992–0.999) method was greater than that of the MODIS IST to the AIRS/AMSU (0.968–0.994). The SST of the AIRS only compared to that of the AIRS/AMSU had a bias of 0.168 K with a RMSE of 0.590 K over the Northern Hemisphere high latitudes and a bias of −0.109 K with a RMSE of 0.852 K over the Southern Hemisphere high latitudes. There was a systematic disagreement between the AIRS retrievals at the boundary of the sea ice, because the AIRS only algorithm utilized a less accurate GCM forecast over the seasonally varying frozen oceans than the microwave data. The three data sets (MODIS, AIRS/AMSU and AIRS only) showed significant warming rates (2.3 ± 1.7 ~ 2.8 ± 1.9 K decade−1) in the northern high regions (70–80° N) as expected from the ice-albedo feedback. The systematic temperature disagreement associated with surface type classification had an impact on the resulting temperature trends.

Compositional diapirism as the origin of the low‐albedo terrain and vaporization at midlatitude on Ceres

AbstractRecent observations of Ceres, made using the Heterodyne Instrument for the Far Infrared on board the European Space Agency's Herschel Space Observatory, have shown that water vapor is emanated from the low‐albedo midlatitude regions. Based on the supposition that some dark spots on Europa may be caused by diapirism, we explored whether Ceres' environment also can induce compositional diapirism, and whether an upwelling diapir could explain the origin and distribution of the dark spots and vaporization of Ceres. If the density of the rock that constitutes Ceres is around 2700 kg m−3, the undifferentiated crust is stable over geological time periods at less than 180 K. At a surface temperature of 170 K, a diapir can reach the surface if the crust is a few tens of kilometers thick. Alternatively, if the surface temperature is 150 K, a large contrast in viscosity would prevent diapirs from reaching the surface. The relatively moderate surface temperature in the midlatitude regions of Ceres may be the reason for the formation of dark terrains occurring only in such areas. Our finite difference calculations do not show that diapirism melts the surface ice because the temperature gradient changes very little. However, if the observed vapor emission is caused by the sublimation of fresh ice, compositional diapirism could be the mechanism that transports the fresh ice to the surface. In addition to other mechanisms such as cryovolcanism, diapirism is a valid hypothesis for explaining the dark terrain and vapor emissions of Ceres.

Investigating the role of multi-spectral and near surface temperature and humidity data to improve precipitation detection at high latitudes

Accurate estimation of global precipitation is critical for the study of the earth in a changing climate. It is generally understood that instantaneous retrieval of precipitation using microwave sensors is more accurate in the tropics and mid latitudes, but the retrievals become difficult and uncertain at higher latitude and over frozen land. In the lack of reliable microwave-based precipitation estimates at high latitudes, retrievals from a single infrared band are commonly used as an alternative to fill the missing gaps. The present study shows that multi-spectral infrared, near-surface air temperature, and near-surface humidity data can add useful information to that obtained from a single infrared band and can significantly improve delineating precipitating from non-precipitating scenes, especially at higher latitudes over land. The role of surface air temperature and humidity is found to be more effective at higher latitudes, but multispectral data is effective across all latitudes. The study is performed using 4years (2007–2010) of collocated multi-spectral data from the Moderate Resolution Imaging Spectroradiometer (MODIS), surface temperature and humidity data from the European Center for Medium Range Weather Forecast (ECMWF) analysis, and reference precipitation data from CloudSat, which can detect even very light precipitation within 80°S–80°N.

Combination of multi-sensor remote sensing data for drought monitoring over Southwest China

Drought is one of the most frequent climate-related disasters occurring in Southwest China, where the occurrence of drought is complex because of the varied landforms, climates and vegetation types. To monitor the comprehensive information of drought from meteorological to vegetation aspects, this paper intended to propose the optimized meteorological drought index (OMDI) and the optimized vegetation drought index (OVDI) from multi-source satellite data to monitor drought in three bio-climate regions of Southwest China. The OMDI and OVDI were integrated with parameters such as precipitation, temperature, soil moisture and vegetation information, which were derived from Tropical Rainfall Measuring Mission (TRMM), Moderate Resolution Imaging Spectroradiometer Land Surface Temperature (MODIS LST), AMSR-E Soil Moisture (AMSR-E SM), the soil moisture product of China Land Soil Moisture Assimilation System (CLSMAS), and MODIS Normalized Difference Vegetation Index (MODIS NDVI), respectively. Different sources of satellite data for one parameter were compared with in situ drought indices in order to select the best data source to derive the OMDI and OVDI. The Constrained Optimization method was adopted to determine the optimal weights of each satellite-based index generating combined drought indices. The result showed that the highest positive correlation and lowest root mean square error (RMSE) between the OMDI and 1-month standardized precipitation evapotranspiration index (SPEI-1) was found in three regions of Southwest China, suggesting that the OMDI was a good index in monitoring meteorological drought; in contrast, the OVDI was best correlated to 3-month SPEI (SPEI-3), and had similar trend with soil relative water content (RWC) in temporal scale, suggesting it a potential indicator of agricultural drought. The spatial patterns of OMDI and OVDI along with the comparisons of SPEI-1 and SPEI-3 for different months in one year or one month in different years showed significantly varied drought locations and areas, demonstrating regional and seasonal fluctuations, and suggesting that drought in Southwest China should be monitored in seasonal and regional level, and more fine distinctions of seasons and regions need to be considered in the future studies of this area.

One‐dimensional soil temperature simulation with Common Land Model by assimilating in situ observations and MODISLST with the ensemble particle filter

AbstractSoil temperature plays an important role in hydrology, agriculture, and meteorology. In order to improve the accuracy of soil temperature simulation, a soil temperature data assimilation system was developed based on the Ensemble Particle Filter (EnPF) and the Common Land Model (CLM), and then applied in the Walnut Gulch Experimental Watershed (WGEW) in Arizona, United States. Surface soil temperature in situ observations and Moderate Resolution Imaging Spectroradiometer Land Surface Temperature (MODIS LST) data were assimilated into the system. In this study, four different assimilation experiments were conducted: (1) assimilating in situ observations of instantaneous surface soil temperature each hour, (2) assimilating in situ observations of instantaneous surface soil temperature once per day, (3) assimilating verified MODIS LST once per day, and (4) assimilating original MODIS LST once per day. These four experiments reflect a transition from high‐quality and more frequent in situ observations to lower quality and less frequent remote sensing data in the data assimilation system. The results from these four experiments show that the assimilated results are better than the simulated results without assimilation at all layers except the bottom layer, while the superiority gradually diminishes as the quality and frequency of the observations decrease. This demonstrates that remote sensing data can be assimilated using the ensemble particle filter in poorly gauged catchments to obtain highly accurate soil variables (e.g., soil moisture, soil temperature). Meanwhile, the results also demonstrate that the ensemble particle filter is effective in assimilating soil temperature observations to improve simulations, but the performance of the data assimilation method is affected by the frequency of assimilation and the quality of the input data.