scholarly journals A New Model to Downscale Urban and Rural Surface and Air Temperatures Evaluated in Shanghai, China

2018 ◽  
Vol 57 (10) ◽  
pp. 2267-2283 ◽  
Author(s):  
Dongwei Liu ◽  
C. S. B. Grimmond ◽  
Jianguo Tan ◽  
Xiangyu Ao ◽  
Jie Peng ◽  
...  
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Spatial Resolution ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Wave Radiation ◽  
Climate Services ◽  
Near Surface ◽  
Surface Temperatures ◽  
Air Temperatures

AbstractA simple model, the Surface Temperature and Near-Surface Air Temperature (at 2 m) Model (TsT2m), is developed to downscale numerical model output (such as from ECMWF) to obtain higher-temporal- and higher-spatial-resolution surface and near-surface air temperature. It is evaluated in Shanghai, China. Surface temperature (Ts) and near-surface air temperature (Ta) submodels account for variations in land cover and their different thermal properties, resulting in spatial variations of surface and air temperature. The net all-wave radiation parameterization (NARP) scheme is used to compute net wave radiation for the surface temperature submodel, the objective hysteresis model (OHM) is used to calculate the net storage heat fluxes, and the surface temperature is obtained by the force-restore method. The near-surface air temperature submodel considers the horizontal and vertical energy changes for a column of well-mixed air above the surface. Modeled surface temperatures reproduce the general pattern of MODIS images well, while providing more detailed patterns of the surface urban heat island. However, the simulated surface temperatures capture the warmer urban land cover and are 10.3°C warmer on average than those derived from the coarser MODIS data. For other land-cover types, values are more similar. Downscaled, higher-temporal- and higher-spatial-resolution air temperatures are compared to observations at 110 automatic weather stations across Shanghai. After downscaling with TsT2m, the average forecast accuracy of near-surface air temperature is improved by about 20%. The scheme developed has considerable potential for prediction and mitigation of urban climate conditions, particularly for weather and climate services related to heat stress.

scholarly journals Intercomparison of Surface Temperatures from AIRS, MERRA, and MERRA-2 with NOAA and GC-Net Weather Stations at Summit, Greenland

2018 ◽  
Vol 57 (5) ◽  
pp. 1231-1245 ◽  
Author(s):  
Thomas J. Hearty ◽  
Jae N. Lee ◽  
Dong L. Wu ◽  
Richard Cullather ◽  
John M. Blaisdell ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Cold Season ◽  
Near Surface ◽  
Surface Temperatures ◽  
Air Temperatures ◽  
Weather Stations ◽  
The Difference ◽  
Temperature Inversions

AbstractThe surface skin and air temperatures reported by the Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit-A (AIRS/AMSU-A), the Modern-Era Retrospective Analysis for Research and Applications (MERRA), and MERRA-2 at Summit, Greenland, are compared with near-surface air temperatures measured at National Oceanic and Atmospheric Administration (NOAA) and Greenland Climate Network (GC-Net) weather stations. The AIRS/AMSU-A surface skin temperature (TS) is best correlated with the NOAA 2-m air temperature (T2M) but tends to be colder than the station measurements. The difference may be the result of the frequent near-surface temperature inversions in the region. The AIRS/AMSU-A surface air temperature (SAT) is also correlated with the NOAA T2M but has a warm bias during the cold season and a larger standard error than the surface temperature. The extrapolation of the temperature profile to calculate the AIRS SAT may not be valid for the strongest inversions. The GC-Net temperature sensors are not held at fixed heights throughout the year; however, they are typically closer to the surface than the NOAA station sensors. Comparing the lapse rates at the two stations shows that it is larger closer to the surface. The difference between the AIRS/AMSU-A SAT and TS is sensitive to near-surface inversions and tends to measure stronger inversions than both stations. The AIRS/AMSU-A may be sampling a thicker layer than either station. The MERRA-2 surface and near-surface temperatures show improvements over MERRA but little sensitivity to near-surface temperature inversions.

scholarly journals Near–surface air temperature and snow skin temperature comparison from CREST-SAFE station data with MODIS land surface temperature data

2015 ◽  
Vol 12 (8) ◽  
pp. 7665-7687 ◽  
Author(s):  
C. L. Pérez Díaz ◽  
T. Lakhankar ◽  
P. Romanov ◽  
J. Muñoz ◽  
R. Khanbilvardi ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Skin Temperature ◽  
Air Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Hydrological Cycle ◽  
Critical Role ◽  
Surface Air Temperature ◽  
Balance Model ◽  
Near Surface

Abstract. Land Surface Temperature (LST) is a key variable (commonly studied to understand the hydrological cycle) that helps drive the energy balance and water exchange between the Earth's surface and its atmosphere. One observable constituent of much importance in the land surface water balance model is snow. Snow cover plays a critical role in the regional to global scale hydrological cycle because rain-on-snow with warm air temperatures accelerates rapid snow-melt, which is responsible for the majority of the spring floods. Accurate information on near-surface air temperature (T-air) and snow skin temperature (T-skin) helps us comprehend the energy and water balances in the Earth's hydrological cycle. T-skin is critical in estimating latent and sensible heat fluxes over snow covered areas because incoming and outgoing radiation fluxes from the snow mass and the air temperature above make it different from the average snowpack temperature. This study investigates the correlation between MODerate resolution Imaging Spectroradiometer (MODIS) LST data and observed T-air and T-skin data from NOAA-CREST-Snow Analysis and Field Experiment (CREST-SAFE) for the winters of 2013 and 2014. LST satellite validation is imperative because high-latitude regions are significantly affected by climate warming and there is a need to aid existing meteorological station networks with the spatially continuous measurements provided by satellites. Results indicate that near-surface air temperature correlates better than snow skin temperature with MODIS LST data. Additional findings show that there is a negative trend demonstrating that the air minus snow skin temperature difference is inversely proportional to cloud cover. To a lesser extent, it will be examined whether the surface properties at the site are representative for the LST properties within the instrument field of view.

Recent Trends in Land Surface Temperature on the Tibetan Plateau

2006 ◽  
Vol 19 (12) ◽  
pp. 2995-3003 ◽  
Author(s):  
Yuichiro Oku ◽  
Hirohiko Ishikawa ◽  
Shigenori Haginoya ◽  
Yaoming Ma
Keyword(s):  
Tibetan Plateau ◽  
Surface Temperature ◽  
Air Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Precipitation Amount ◽  
Surface Air Temperature ◽  
The Tibetan Plateau ◽  
Near Surface ◽  
Diurnal Range

Abstract The diurnal, seasonal, and interannual variations in land surface temperature (LST) on the Tibetan Plateau from 1996 to 2002 are analyzed using the hourly LST dataset obtained by Japanese Geostationary Meteorological Satellite 5 (GMS-5) observations. Comparing LST retrieved from GMS-5 with independent precipitation amount data demonstrates the consistent and complementary relationship between them. The results indicate an increase in the LST over this period. The daily minimum has risen faster than the daily maximum, resulting in a narrowing of the diurnal range of LST. This is in agreement with the observed trends in both global and plateau near-surface air temperature. Since the near-surface air temperature is mainly controlled by LST, this result ensures a warming trend in near-surface air temperature.

Study on Urban Thermal Environment based on Diurnal Temperature Range

2020 ◽  
Author(s):  
Zheng Guo ◽  
Miaomiao Cheng
Keyword(s):  
Surface Temperature ◽  
Air Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Thermal Environment ◽  
Surface Air Temperature ◽  
Heat Island ◽  
Near Surface ◽  
Diurnal Range ◽  
Urban Thermal Environment

<p>Diurnal temperature range (includes land surface temperature diurnal range and near surface air temperature diurnal range) is an important meteorological parameter, which is a very important factor in the field of the urban thermal environmental. Nowadays, the research of urban thermal environment mainly focused on surface heat island and canopy heat island.</p><p>Based on analysis of the current status of city thermal environment. Firstly, a method was proposed to obtain near surface air temperature diurnal range in this study, difference of land surface temperature between day and night were introduced into the improved temperature vegetation index feature space based on remote sensing data. Secondly, compared with the district administrative division, we analyzed the spatial and temporal distribution characteristics of the diurnal range of land surface temperature and near surface air temperature.</p><p>The conclusions of this study are as follows:</p><p>1 During 2003-2012s, the land surface temperature and near surface air temperature diurnal range of Beijing were fluctuating upward. The rising trend of the near surface air temperature diurnal range was more significant than land surface temperature diurnal range. In addition, the rise and decline of land surface temperature and near surface air temperature diurnal range in different districts were different. In the six city districts, the land surface temperature and near surface air temperature diurnal range in the six areas of the city were mainly downward. The decline trend of near surface air temperature diurnal range was more significant than land surface temperature diurnal range.</p><p>2 During 2003-2012s, the land surface temperature and near surface air temperature diurnal range of Beijing with similar characteristics in spatial distribution, with higher distribution land surface temperature and near surface air temperature diurnal range in urban area and with lower distribution of land surface temperature and near surface air temperature diurnal range in the Northwest Mountainous area and the area of Miyun reservoir.</p>

scholarly journals An evaluation of the impact of aerosol particles on weather forecasts from a biomass burning aerosol event over the Midwestern United States: observational-based analysis of surface temperature

2016 ◽  
Vol 16 (10) ◽  
pp. 6475-6494 ◽  
Author(s):  
Jianglong Zhang ◽  
Jeffrey S. Reid ◽  
Matthew Christensen ◽  
Angela Benedetti
Keyword(s):  
United States ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Cooling Efficiency ◽  
Surface Cooling ◽  
Near Surface ◽  
Smoke Aerosol ◽  
Weather Forecasts ◽  
Air Temperatures ◽  
Daily Changes

Abstract. A major continental-scale biomass burning smoke event from 28–30 June 2015, spanning central Canada through the eastern seaboard of the United States, resulted in unforecasted drops in daytime high surface temperatures on the order of 2–5  °C in the upper Midwest. This event, with strong smoke gradients and largely cloud-free conditions, provides a natural laboratory to study how aerosol radiative effects may influence numerical weather prediction (NWP) forecast outcomes. Here, we describe the nature of this smoke event and evaluate the differences in observed near-surface air temperatures between Bismarck (clear) and Grand Forks (overcast smoke), to evaluate to what degree solar radiation forcing from a smoke plume introduces daytime surface cooling, and how this affects model bias in forecasts and analyses. For this event, mid-visible (550 nm) smoke aerosol optical thickness (AOT, τ) reached values above 5. A direct surface cooling efficiency of −1.5 °C per unit AOT (at 550 nm, τ550) was found. A further analysis of European Centre for Medium-Range Weather Forecasts (ECMWF), National Centers for Environmental Prediction (NCEP), United Kingdom Meteorological Office (UKMO) near-surface air temperature forecasts for up to 54 h as a function of Moderate Resolution Imaging Spectroradiometer (MODIS) Dark Target AOT data across more than 400 surface stations, also indicated the presence of the daytime aerosol direct cooling effect, but suggested a smaller aerosol direct surface cooling efficiency with magnitude on the order of −0.25 to −1.0 °C per unit τ550. In addition, using observations from the surface stations, uncertainties in near-surface air temperatures from ECMWF, NCEP, and UKMO model runs are estimated. This study further suggests that significant daily changes in τ550 above 1, at which the smoke-aerosol-induced direct surface cooling effect could be comparable in magnitude with model uncertainties, are rare events on a global scale. Thus, incorporating a more realistic smoke aerosol field into numerical models is currently less likely to significantly improve the accuracy of near-surface air temperature forecasts. However, regions such as eastern China, eastern Russia, India, and portions of the Saharan and Taklamakan deserts, where significant daily changes in AOTs are more frequent, are likely to benefit from including an accurate aerosol analysis into numerical weather forecasts.

scholarly journals Suitability of a constant air temperature lapse rate over an Alpine glacier: testing the Greuell and Böhm model as an alternative

2013 ◽  
Vol 54 (63) ◽  
pp. 120-130 ◽  
Author(s):  
Lene Petersen ◽  
Francesca Pellicciotti ◽  
Inge Juszak ◽  
Marco Carenzo ◽  
Ben Brock
Keyword(s):  
Air Temperature ◽  
Surface Air Temperature ◽  
Ambient Air ◽  
Lapse Rate ◽  
Spatial And Temporal Variability ◽  
Near Surface ◽  
Alpine Glacier ◽  
Temperature Lapse Rate ◽  
Boundary Layer Height ◽  
Air Temperatures

AbstractNear-surface air temperature, typically measured at a height of 2 m, is the most important control on the energy exchange and the melt rate at a snow or ice surface. It is distributed in a simplistic manner in most glacier melt models by using constant linear lapse rates, which poorly represent the actual spatial and temporal variability of air temperature. In this paper, we test a simple thermodynamic model proposed by Greuell and Böhm in 1998 as an alternative, using a new dataset of air temperature measurements from along the flowline of Haut Glacier d’Arolla, Switzerland. The unmodified model performs little better than assuming a constant linear lapse rate. When modified to allow the ratio of the boundary layer height to the bulk heat transfer coefficient to vary along the flowline, the model matches measured air temperatures better, and a further reduction of the root-mean-square error is obtained, although there is still considerable scope for improvement. The modified model is shown to perform best under conditions favourable to the development of katabatic winds – few clouds, positive ambient air temperature, limited influence of synoptic or valley winds and a long fetch – but its performance is poor under cloudy conditions.

Temperate-zone reforestation as a tool for local climate adaptation? 

2021 ◽  
Author(s):  
Kimberly Novick
Keyword(s):  
Surface Temperature ◽  
Air Temperature ◽  
Climate Adaptation ◽  
Heat Waves ◽  
Surface Air Temperature ◽  
Climate Mitigation ◽  
Surface Cooling ◽  
Local Cooling ◽  
Near Surface ◽  
Local Climate

<p>In addition to dramatic reductions to anthropogenic greenhouse gas emissions, most pathways for limiting global warming to less than 2 degrees C rely on managed alterations to the land surface designed to increase land carbon uptake and storage (so-called “natural climate solutions”, or NCS). Reforestation is the NCS with the largest estimated climate mitigation potential, and at least in energy-limited temperate climates, evidence is mounting that transitions from short-stature ecosystems (croplands, grasslands) to forests substantially reduce surface temperature. In this way, reforestation, at least in some places, may also represent a useful tool for local climate adaptation. However, existing work on the topic has tended to focus on how reforestation affects mean annual and seasonal surface temperature, with comparatively less attention paid to the biophysical impacts of reforestation when local cooling would be most beneficial (i.e. at mid-day, and especially droughts and heat waves). Moreover, while surface temperature is a critical driver of ecosystem processes, arguably the near-surface air temperature is the more relevant target for climate adaptation. The duality between reforestation impacts on surface and air temperature has historically been challenging to deconvolve, and thus we do not yet understand the extent to which forest surface cooling extends to the air. In this talk, new strategies are discussed for blending flux tower data and remote sensing observations to uncover the links between reforestation, surface energy balance, and near-surface air temperature dynamics, with a particular emphasis on how plant water use strategies mediate these relationships during summer days and periods of hydrologic stress.  </p>

Analyzing Near Surface Temperature Inversions Across the Greenland Ice Sheet Using In-situ, Remote Sensing, and Reanalysis Data

2020 ◽  
Author(s):  
Alden Adolph ◽  
Wesley Brown ◽  
Karina Zikan ◽  
Robert Fausto
Keyword(s):  
Surface Temperature ◽  
Energy Exchange ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Near Surface ◽  
Surface Temperatures ◽  
Air Temperatures ◽  
Exchange Processes ◽  
Temperature Inversions

<p>As Arctic temperatures have increased, the Greenland Ice Sheet has exhibited a negative mass balance, with a substantial and increasing fraction of mass loss due to surface melt. Understanding surface energy exchange processes in Greenland is critical for our ability to predict changes in mass balance. In-situ and remotely sensed surface temperatures are useful for monitoring trends, melt events, and surface energy balance processes, but these observations are complicated by the fact that surface temperatures and near surface air temperatures can significantly differ due to the presence of inversions that exist across the Arctic. Our previous work shows that even in the summer, very near surface inversions are present between the 2m air and surface temperatures a majority of the time at Summit, Greenland. In this study, we expand upon these results and combine a variety of data sources to quantify differences between surface snow/ice temperatures and 2m air temperatures across the Greenland Ice Sheet and investigate controls on the magnitude of these near surface temperature inversions. In-situ temperatures, wind speed, specific humidity, and albedo data are provided from automatic weather stations operated by the Programme for Monitoring of the Greenland Ice Sheet (PROMICE). We use the Clouds and the Earth's Radiant Energy System (CERES) cloud area fraction data to analyze effects of cloud presence on near surface temperature gradients. The in-situ temperatures are compared to Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) and Moderate Resolution Imaging Spectrometer (MODIS) ice surface temperature data to extend findings across the ice sheet. Using PROMICE in-situ data from 2015, we find that these 2m temperature inversions are present 77% of the time, with a median strength of 1.7°C. The data confirm that the presence of clouds weakens inversions. Initial results indicate a RMSE of 3.9°C between MERRA-2 and PROMICE 2m air temperature, and a RMSE of 5.6°C between the two datasets for surface temperature. Improved understanding of controls on near surface inversions is important for use of remotely sensed snow surface temperatures and for modeling of surface mass and energy exchange processes.</p>

scholarly journals Changes of Variability in Response to Increasing Greenhouse Gases. Part I: Temperature

2007 ◽  
Vol 20 (21) ◽  
pp. 5455-5467 ◽  
Author(s):  
R. J. Stouffer ◽  
R. T. Wetherald
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Annual Data ◽  
Tropospheric Temperature ◽  
High Latitudes ◽  
Near Surface ◽  
Temperature Variance ◽  
General Reduction

Abstract This study documents the temperature variance change in two different versions of a coupled ocean–atmosphere general circulation model forced with estimates of future increases of greenhouse gas (GHG) and aerosol concentrations. The variance changes are examined using an ensemble of 8 transient integrations for the older model version and 10 transient integrations for the newer one. Monthly and annual data are used to compute the mean and variance changes. Emphasis is placed upon computing and analyzing the variance changes for the middle of the twenty-first century and compared with those found in a control integration. The large-scale variance of lower-tropospheric temperature (including surface air temperature) generally decreases in high latitudes particularly during fall due to a delayed onset of sea ice as the climate warms. Sea ice acts to insolate the atmosphere from the much larger heat capacity of the ocean. Therefore, the near-surface temperature variance tends to be larger over the sea ice–covered regions, than the nearby ice-free regions. The near-surface temperature variance also decreases during the winter and spring due to a general reduction in the extent of sea ice during winter and spring. Changes in storminess were also examined and were found to have relatively little effect upon the reduction of temperature variance. Generally small changes of surface air temperature variance occurred in low and midlatitudes over both land and oceanic areas year-round. An exception to this was a general reduction of variance in the equatorial Pacific Ocean for the newer model. Small increases in the surface air temperature variance occur in mid- to high latitudes during the summer months, suggesting the possibility of more frequent and longer-lasting heat waves in response to increasing GHGs.

scholarly journals Near-surface thermal stratification during summer at Summit, Greenland, and its relation to MODIS-derived surface temperatures

2017 ◽  
Author(s):  
Alden C. Adolph ◽  
Mary R. Albert ◽  
Dorothy K. Hall
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Skin Temperature ◽  
Air Temperature ◽  
The Arctic ◽  
Cold Bias ◽  
Near Surface ◽  
Surface Temperatures ◽  
In Situ Ir

Abstract. As rapid warming of the Arctic occurs, it is imperative that climate indicators such as temperature be monitored over large areas to understand and predict the effects of climate changes. Temperatures are traditionally tracked using in situ 2 m air temperatures, but in remote locations where few ground-based measurements exist, such as on the Greenland Ice Sheet, temperatures over large areas are assessed using remote sensing techniques. Because of the presence of surface-based temperature inversions in ice-covered areas, differences between 2 m air temperature and the temperature of the actual snow surface (referred to as skin temperature) can be significant and are particularly relevant when considering validation and application of remote sensing temperature data. We present results from a field campaign extending from 8 June through 18 July 2015, near Summit Station in Greenland to study surface temperature using the following measurements: skin temperature measured by an infrared (IR) sensor, thermochrons, and thermocouples; 2 m air temperature measured by a NOAA meteorological station; and a MODerate-resolution Imaging Spectroradiometer (MODIS) surface temperature product. Our data indicate that 2 m air temperature is often significantly higher than snow skin temperature measured in-situ, and this finding may account for apparent biases in previous surface temperature studies of MODIS products that used 2 m air temperature for validation. This inversion is present during summer months when incoming solar radiation and wind speed are both low. As compared to our in-situ IR skin temperature measurements, after additional cloud masking, the MOD/MYD11 Collection 6 surface-temperature standard product has an RMSE of 1.0 °C, spanning a range of temperatures from −35 °C to −5 °C. For our study area and time series, MODIS surface temperature products agree with skin surface temperatures better than previous studies indicated, especially at temperatures below −20 °C where other studies found a significant cold bias. The apparent cold bias present in others’ comparison of 2 m air temperature and MODIS surface temperature is perhaps a result of the near-surface temperature inversion that our data demonstrate. Further investigation of how in-situ IR skin temperatures compare to MODIS surface temperature at lower temperatures (below −35 °C) is warranted to determine if this cold bias does indeed exist.

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