Near-surface Temperature Lapse Rates Research Articles

Estimation on the hourly near-surface temperature lapse rate and its time-varying characteristics

Since much of the current researches have focused on daily, monthly or annual near-surface (2 m) temperature lapse rate (NSTLR), there is little guidance on best estimation practices and analyses of time-varying characteristics for the hourly NSTLR. To estimate hourly NSTLR and identify its time-varying characteristics accurately and objectively, this study proposed a robust estimation strategy based on IGGIII equivalent weight using multiple linear regression models. The accuracy and reliability of the proposed method was verified. The results show that the robust estimation strategy can further improve the hourly NSTLR solution accuracy relative to the least square (LSQ) method, especially in the time period of relatively high temperature. The hourly NSTLR was positively correlated with temperature, with a 24-h average maximum of 0.604 °C/100 m at universal time coordinated (UTC) 7.2 h and minimum of 0.284 °C/100 m at UTC 20.5 h, respectively. Throughout the year, the NSTLR was the largest from June to August, with an average median of around 0.492 °C/100 m. However, from November to the following January, the NSTLR value was the smallest, with a mean median of about 0.323 °C/100 m. In addition, the hourly NSTLR values were essentially less than the constant value of 0.65 °C/100 m. When the hourly NSTLR estimated based on the proposed method was applied to the temperature interpolation, the interpolation accuracies at the highest altitude (1545 m) and other meteorological stations (below 310 m) can increase by 22.4 % and 8.1 %, respectively, relative to the hourly NSTLR calculated by the LSQ method, and increased by 55.6 % and 13.0 %, respectively, relative to the no-NSTLR correction. The results are important for the fine establishment of high spatiotemporal resolution temperature fields and for the study of climatic phenomena characterized with rapid spatiotemporal variation.

Estimation on the Hourly Distribution of Near-Surface Temperature Lapse Rate Under Winter Clear-Sky Conditions

Estimation on the Hourly Distribution of Near-Surface Temperature Lapse Rate Under Winter Clear-Sky Conditions

A new approach to LST modeling and normalization under clear-sky conditions based on a local optimization strategy

ABSTRACT The normalization of LST relative to environmental parameters is of great importance in various environmental applications. The purpose of this study was to develop a new approach for LST normalization relative to environmental variables. These included topographic variables (i.e. solar irradiance and near-surface temperature lapse rate (NSTLR)) as well as biophysical properties (i.e. vegetation, wetness, and albedo). The study was conducted in two phases, namely (1) using global and (2) local optimization strategies to calculate the regression coefficients of environmental variables in the partial least squares regression (PLSR) and build the non-linear linking model in the random forest regression (RFR). The RMSEs between actual LST and modeled LST based on the global and local optimization strategies using PLSR (RFR) were 2.202 (0.935) and 0.939 (0.835) °C, respectively. The results showed that RFR had higher efficiency than PLSR in normalizing LST. Moreover, the local optimization method outperformed the global optimization method in terms of normalization accuracy. The results of this study could be very useful in many environmental applications such as identifying thermal anomalies, and surface anthropogenic heat island modeling.

Climate of the Marrakech High Atlas, Morocco: Temperature lapse rates and precipitation gradient from piedmont to summits

ABSTRACT Understanding mountain climates poses many challenges, because difficult terrain leads to a sparsity of weather stations and therefore poor data availability, meaning the detailed information required to understand these complex systems is lacking. Here, we analyze eleven years of half-hourly climate observations from the Joint International Laboratory LMI-TREMA (Télédétection et Ressources en Eau en Méditerranée semi-Aride) network of weather stations in the Marrakech High Atlas, Morocco, providing detailed information about the climate in this area. Our analysis shows the mean annual near-surface temperature lapse rate is −4.63°C km−1, with an uncertainty range of −4.39 to −4.85°C km−1, lower than the standard environmental temperature lapse rate. Mean temperature lapse rates vary from −3.67°C to −5.21°C km−1 monthly, and throughout the day from −2.75°C to −7.1°C km−1, which has important implications for understanding snowpack variations at the highest elevations. Understanding precipitation is inherently complex, but our analysis shows that mean annual precipitation increases by 166 mm km−1 (150.6 to 183.7 mm km−1) with a significant snow component at the highest elevations. This analysis improves our understanding of the mountain climate system with new regional temperate lapse rates and precipitation gradients, having the potential to improve gridded climatologies and climate models, with relevance for the wider High Atlas region.

Unraveling the distribution patterns of near-surface temperature lapse rates in the Northwestern Kunlun Mountains

Unraveling the distribution patterns of near-surface temperature lapse rates in the Northwestern Kunlun Mountains

Analysis of Near-Surface Temperature Lapse Rates in Mountain Ecosystems of Northern Mexico Using Landsat-8 Satellite Images and ECOSTRESS

Mountain ecosystems provide environmental goods, which can be threatened by climate change. Near-Surface Temperature Lapse Rate (NSTLR) is an essential factor used for thermal and hydrological analysis in mountain ecosystems. The aims of the present study were to estimate NSTLR and to identify its relationship with aspect, Local solar zenith angle (LSZA) and Evaporative Stress Index (ESI) for two seasons of the year in a mountain ecosystem at the North of Mexico. Normalized Land Surface Temperature (NLST) was estimated using environmental and topographical variables. LSZA was calculated from slope to consider the effect of solar position. NSTLR was estimated through simple linear models. Observed NSTLR was 9.4 °C km−1 for the winter and 14.3 °C km−1 for the summer. Our results showed variation in NSTLR by season. In addition, aspect, LSZA and ESI also influenced NSTLR regulation. In addition, Northwest and West aspects exhibited the highest NSTLR. LSZA angles closest to 90° were related with a decrease in NSTLR for both seasons. Finally, ESI values associated with less evaporative stress were related to lower NSTLR. These results suggest potential of Landsat-8 LST and ECOSTRESS ESI to capture interactions of temperature, topography, and water stress in complex ecosystems.

Snow cover mapping, topographic controls and integration of meteorological data sets in Din-Gad Basin, Central Himalaya

Din-Gad basin, located in central Himalaya is occupied by the Dokriani glacier in upper reaches. Landsat TM, OLI and Sentinel MSI data sets of seven years from 2009 to 2011 and 2013 to 2016 are utilized to map the areal extent of snow-cover, its seasonal variability and topographical controls (elevation, aspect, and slope). Coefficient of Variation (CV) in Snow Cover Area (SCA) below the elevation of ~5000 m asl is high (~2.0), and is low at higher elevations. CV is also higher for southern as compared to northern aspects. Meteorological data (temperature, relative humidity, and solar radiation) from Automatic Weather Stations (AWSs) is utilized to compute isotherms (~0, 1, and 2 °C) by extrapolation method using Near-surface Temperature Lapse Rate (NSTLR). These data sets are integrated and presented by graphical as well as on Geographical Information System (GIS). Month-wise isotherms closely correspond with snow-cover extent during ablation season, suggesting that the extrapolated temperatures represent a significant proxy for depletion pattern, while month-wise and hourly isotherms deviate largely from the SCA during winter months due to snow events. Elevation zones above 5200 m asl retain snow throughout the year, indicating proximity with Equilibrium Line Altitude (ELA). The effects of Relative Humidity (RH) and solar radiation on melting history during different seasons have also emerged. The proposed methodology is efficient and reliable in terms of estimating the depletion patterns, and deriving the isotherms that can be applied to other comparable snow-covered areas.

A new approach for modeling near surface temperature lapse rate based on normalized land surface temperature data

The modeling of Near-Surface Temperature Lapse Rate (NSTLR) is of great importance in various environmental applications. This study proposed a new approach for modeling the NSTLR based on the Normalized Land Surface Temperature (NLST). A set of remote sensing imagery including Landsat images, MODIS products, and ASTER Digital Elevation Model (DEM), land cover maps, and climatic data recorded in meteorological stations and self-deployed devices located in the three study area were used for modeling and evaluation of NSTLR. First, the Split Window (SW) and Single Channel (SC) algorithms were used to estimate LST, and the spectral indices were used to model surface biophysical characteristics. The solar local incident angle was obtained based on topographic and time conditions for different dates. In the second step, the NSTLR value was calculated based on the LST-DEM feature space at the regional scale. The LST was normalized relative to the surface characteristics based on Random Forest (RF) regression and the NSTLR was calculated based on the NLST-DEM feature space. Finally, the coefficient of determination (R2) and Root Mean Square Error (RMSE) between the modeled NSTLR and the observed NSTLR were calculated to evaluate the accuracy of the modeled NSTLR. The mean values of R2 between DEM and NLST were improved 0.3, 0.42 and 0.35, rather than between DEM and LST for the study area A, B and C, respectively. The R2 and RMSE between the observed NSTLR and the Landsat derived NSTLR based on NLST for the study area A (B, C) were improved 0.30 (0.26, 0.35) and 0.81 (0.80, 0.94) °C Km−1, respectively, rather than the Landsat derived NSTLR based on LST. Also, for the study area A, the R2 and RMSE between the observed NSTLR and the MODIS derived NSTLR based on NLST in spring, summer, autumn and winter were improved 0.17, 0.12, 0.10, and 0.22; and 0.51, 0.44, 0.27, and 0.51 °C Km−1, respectively, rather than the MODIS derived NSTLR based on LST. Model assessment results (R2 and RMSE) and comparing modeled NSTLR (all strategies) with observed NSTLR, for both Landsat and MODIS, showed that the use of NLST instead of LST, significantly improved the accuracy of the obtained NSTLR in the mountainous regions.

MODELING THE IMPACT OF SURFACE CHARACTERISTICS ON THE NEAR SURFACE TEMPERATURE LAPSE RATE

Abstract. Modeling of Near-Surface Temperature Lapse Rate (NSTLR) is very important in various environmental applications. The Land Surface Temperature (LST) is influenced by many properties and conditions including surface biophysical and topographic characteristics. Some researches have considered the LST - Digital Elevation Model (DEM) feature space to model NSTLR. However, the influence of detailed surface characteristics is rare. This study investigated the impact of surface characteristics on the LST-DEM feature space for NSTLR modeling. A set of remote sensing data including Landsat 8 images, MODIS products, and surface features including DEM and land use of the Balikhli-Chay on 01/07/2018, 18/08/2018 and 03/09/2018 were collected and used in this study. First, Split Window (SW) algorithm was used to estimate LST, and spectral indices were employed to model surface biophysical characteristics. Owing to the impact of surface biophysical and topographic characteristics on the LST-DEM feature space, the NSTLR was calculated for different classes of surface biophysical characteristics, land use, and solar local incident angle. The modeled NSTLR values based on the LST-DEM feature space on 01/07/2018, 18/08/2018 and 03/09/2018 were 8.5, 1.5 and 2.4 °C Km−1; respectively. The NSTLR in different classes of surface biophysical characteristics, land use type and topographical parameters were variable between 0.5 to 14 °C Km−1. This clearly showed the dependence of NSTLR on topographic and biophysical conditions. This provides a new way of calculating surface characteristic specific NSTLR.

Reconciling High Glacier Surface Melting in Summer with Air Temperature in the Semi-Arid Zone of Western Himalaya

In Himalaya, the temperature plays a key role in the process of snow and ice melting and, importantly, the precipitation phase changes (i.e., snow or rain). Consequently, in longer period, the melting and temperature gradient determine the state of the Himalayan glaciers. This necessitates the continuous monitoring of glacier surface melting and a well-established meteorological network in the Himalaya. An attempt has been made to study the seasonal and annual (October 2015 to September 2017) characteristics of air temperature, near-surface temperature lapse rate (tlr), in-situ glacier surface melting, and surface melt simulation by temperature-index (T-index) models for Sutri Dhaka Glacier catchment, Lahaul-Spiti region in Western Himalaya. The tlr of the catchment ranges from 0.3 to 6.5 °C km−1, varying on a monthly and seasonal timescale, which suggests the need for avoiding the use of standard environmental lapse rate (SELR ~6.5 °C km−1). The measured and extrapolated average air temperature (tavg) was found to be positive on glacier surface (4500 to 5500 m asl) between June and September (summer). Ablation data calculated for the balance years 2015–16 and 2016–17 shows an average melting of −4.20 ± 0.84 and −3.09 ± 0.62 m w.e., respectively. In compliance with positive air temperature in summer, ablation was also found to be maximum ~88% of total yearly ice melt. When comparing the observed and modelled ablation data with air temperature, we show that the high summer glacier melt was caused by warmer summer air temperature and minimum spells of summer precipitation in the catchment.

Spatio-temporal variability of near-surface air temperature in the Dokriani glacier catchment (DGC), central Himalaya

Air temperature is one of the most important meteorological factors that affect melting of glaciers, distribution of snowfall and rain at higher altitudes in the Himalaya. However, studies on spatio-temporal variability of air temperature in the central Himalaya are limited. In the present study, seasonal and annual characteristics (July 2011 to December 2015) of near-surface temperature and lapse rate in the Dokriani glacier catchment (DGC) of the central Himalaya are investigated using data from three automatic weather stations (AWSs). An attempt is also made to quantify 0 °C isotherm and temperate sustainability over the glacierized area. The results reveal that the average near-surface temperature lapse rate (NSTLR) of the catchment varies from 4.6 to 7.5 °C km−1 during all measurement seasons, suggesting that the standard environmental lapse rate (SELR, 6.5 °C km−1) is not a promising input for realistic glacio-hydrological modeling. The seasonal variability of the NSTLR indicates that the monsoon (warm and humid period) lowers the temperature lapse rate in this catchment due to the presence of high moisture content in the air. The steepest lapse rate is investigated during the pre-monsoon season due to clear and drier weather conditions. In addition to this, the results reveal strong variability in NSTLR at diurnal and sub-diurnal levels, with high variability in the day time and low in the night-time hours. A higher air temperature is examined in the ablation zone of the Dokriani Glacier during the monsoon season (i.e., JJAS: June, July, August, September), while other seasons (pre-monsoon, post-monsoon, winter) show both higher as well as lower temperatures. A large variation in 0 °C isotherm is also observed ranging from 5000 to 5500 m asl during 2012–2015. The present work emphasizes that the study of monthly, seasonal, and annual variability of the NSTLR are very important for glacio-hydrological research in the central Himalaya.

Air temperature variability in the vertical profile over the coastal area of Petuniabukta, central Spitsbergen

AbstractA two-year-long data set of air temperature from four different altitudes above Petuniabukta, central Spitsbergen, was analysed in order to assess the near-surface temperature lapse rates and the relative frequency of air temperature inversion occurrence. From August 2013 to July 2015, air temperatures at adjacent altitudes in Petuniabukta were strongly correlated. The near-surface lapse rates in all three layers differed significantly both from the average lapse rate in the international standard atmosphere (0.65°C 100 m−1) and the lapse rate calculated by linear regression. A pronounced annual cycle was detected in the lowermost air layer (from 23 to 136 m a.s.l.) with a variable near-surface lapse rate in the winter months, while an annual cycle was not apparent in the air layers above 136 m a.s.l. The lowermost layer was also characterized by a notable daily cycle in near-surface lapse rate in spring and autumn. Air temperature inversions occurred in up to 80% of the study period in the air layer below 136 m a.s.l., with the relative frequency being much lower in the other two air layers. The air temperature inversions lasted as long as 139 hours. A case study revealed that one of the strongest air temperature inversions was connected to an area of lower pressure gradients at the 850-hPa pressure level.

Near-Surface Temperature Lapse Rates over Arctic Glaciers and Their Implications for Temperature Downscaling

AbstractDistributed glacier surface melt models are often forced using air temperature fields that are either downscaled from climate models or reanalysis, or extrapolated from station measurements. Typically, the downscaling and/or extrapolation are performed using a constant temperature lapse rate, which is often taken to be the free-air moist adiabatic lapse rate (MALR: 6°–7°C km−1). To explore the validity of this approach, the authors examined altitudinal gradients in daily mean air temperature along six transects across four glaciers in the Canadian high Arctic. The dataset includes over 58 000 daily averaged temperature measurements from 69 sensors covering the period 1988–2007. Temperature lapse rates near glacier surfaces vary on both daily and seasonal time scales, are consistently lower than the MALR (ablation season mean: 4.9°C km−1), and exhibit strong regional covariance. A significant fraction of the daily variability in lapse rates is associated with changes in free-atmospheric temperatures (higher temperatures = lower lapse rates). The temperature fields generated by downscaling point location summit elevation temperatures to the glacier surface using temporally variable lapse rates are a substantial improvement over those generated using the static MALR. These findings suggest that lower near-surface temperature lapse rates can be expected under a warming climate and that the air temperature near the glacier surface is less sensitive to changes in the temperature of the free atmosphere than is generally assumed.

Sensitivity of net mass-balance estimates to near-surface temperature lapse rates when employing the degree-day method to estimate glacier melt

AbstractGlacier mass-balance models that employ the degree-day method of melt modeling are most commonly driven by surface air temperatures that have been downscaled over the area of interest, using digital elevation models and assuming a constant free air lapse rate that is often taken to be the moist adiabatic lapse rate (MALR: –6.5°Ckm–1). Air-temperature lapse rates measured over melting glacier surface are, however, consistently less steep than free air values and have been shown to vary systematically with lower-tropospheric temperatures. In this study, the implications of including a variable near-surface lapse rate in a 26 year (1980–2006) degree-day model simulation of the surface mass balance of Devon Ice Cap, Nunavut, Canada, are examined and compared with estimates derived from surface air temperatures downscaled using a constant near-surface lapse rate equal to the measured summer mean (–4.9°Ckm–1) and the MALR. Our results show that degree-day models are highly sensitive to the choice of lapse rate. When compared with 23 years of surface mass-balance measurements from the northwest sector of the ice cap, model estimates are significantly better when surface air temperatures are downscaled using a modeled daily lapse rate rather than a constant lapse equal to either the summer mean or the MALR.

Spray Irrigation Effects on Surface-Layer Stability in an Experimental Citrus Orchard during Winter Freezes

Observations taken by two surface radiation and energy budget stations deployed in the University of Florida/ Institute for Food and Agricultural Service experimental citrus orchard in Gainesville, Florida, have been analyzed to identify the effects of sprayer irrigation on thermal stability and circulation processes within the orchard during three 1992 winter freeze episodes. Lapse rates of temperature observed from a micrometeorological tower near the center of the orchard were also recorded during periods of irrigation for incorporation into the analysis. Comparisons of the near-surface temperature lapse rates observed with the two energy budget stations show consistency between the two sites and with the tower-based lapse rates taken over a vertical layer from 1.5 to 15 m above ground level. A theoretical framework was developed that demonstrates that turbulent-scale processes originating within the canopy, driven by latent heat release associated with condensation and freezing processes from water vapor and liquid water released from sprayer nozzles, can destabilize lapse rates and promote warm air mixing above the orchard canopy. The orchard data were then analyzed in the context of the theory for evidence of local overturning and displacement of surface-layer air, with warmer air from aloft driven by locally buoyant plumes generated by water vapor injected into the orchard during the irrigation periods. It was found that surface-layer lapse rates were lower during irrigation periods than under similar conditions when irrigation was not occurring, indicating a greater degree of vertical mixing of surface-layer air with air from above treetops, as a result of local convective overturning induced by the condensation heating of water vapor released at the nozzles of the sprinklers. This provides an additional explanation to the well-accepted heat of fusion release effect, of how undertree irrigation of a citrus orchard during a freeze period helps protect crops against frost damage.