Soil moisture influenced the variability of air temperature and oasis effect in a large inland basin of an arid region

2021 ◽  
Author(s):  
Xingming Hao ◽  
Haichao Hao ◽  
Jingjing Zhang
Keyword(s):  
Soil Moisture ◽  
Air Temperature ◽  
Arid Region ◽  
Oasis Effect

scholarly journals Soil moisture controlled the variability of air temperature and oasis effect in a large inland basin in arid region

2020 ◽  
Author(s):  
Xingming Hao ◽  
Haochao Hao ◽  
Jingjing Zhang
Keyword(s):  
Soil Moisture ◽  
Air Temperature ◽  
Arid Region ◽  
Oasis Effect

scholarly journals Evaluation and Comparison of Noah and Pleim–Xiu Land Surface Models in MM5 Using GÖTE2001 Data: Spatial and Temporal Variations in Near-Surface Air Temperature

2007 ◽  
Vol 46 (10) ◽  
pp. 1587-1605 ◽  
Author(s):  
J-F. Miao ◽  
D. Chen ◽  
K. Borne
Keyword(s):  
Soil Moisture ◽  
Air Temperature ◽  
Land Surface ◽  
Model Performance ◽  
Surface Air Temperature ◽  
Near Surface ◽  
Surface Models ◽  
Urban Heat ◽  
Soil Moisture Initialization ◽  
Evident Difference

Abstract In this study, the performance of two advanced land surface models (LSMs; Noah LSM and Pleim–Xiu LSM) coupled with the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5), version 3.7.2, in simulating the near-surface air temperature in the greater Göteborg area in Sweden is evaluated and compared using the GÖTE2001 field campaign data. Further, the effects of different planetary boundary layer schemes [Eta and Medium-Range Forecast (MRF) PBLs] for Noah LSM and soil moisture initialization approaches for Pleim–Xiu LSM are investigated. The investigation focuses on the evaluation and comparison of diurnal cycle intensity and maximum and minimum temperatures, as well as the urban heat island during the daytime and nighttime under the clear-sky and cloudy/rainy weather conditions for different experimental schemes. The results indicate that 1) there is an evident difference between Noah LSM and Pleim–Xiu LSM in simulating the near-surface air temperature, especially in the modeled urban heat island; 2) there is no evident difference in the model performance between the Eta PBL and MRF PBL coupled with the Noah LSM; and 3) soil moisture initialization is of crucial importance for model performance in the Pleim–Xiu LSM. In addition, owing to the recent release of MM5, version 3.7.3, some experiments done with version 3.7.2 were repeated to reveal the effects of the modifications in the Noah LSM and Pleim–Xiu LSM. The modification to longwave radiation parameterizations in Noah LSM significantly improves model performance while the adjustment of emissivity, one of the vegetation properties, affects Pleim–Xiu LSM performance to a larger extent. The study suggests that improvements both in Noah LSM physics and in Pleim–Xiu LSM initialization of soil moisture and parameterization of vegetation properties are important.

Ecological responses of Stipa steppe in Inner Mongolia to experimentally increased temperature and precipitation. 4. Carbon exchange

2018 ◽  
Vol 40 (2) ◽  
pp. 159 ◽  
Author(s):  
Luomeng Chao ◽  
Zhiqiang Wan ◽  
Yulong Yan ◽  
Rui Gu ◽  
Yali Chen ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Air Temperature ◽  
Inner Mongolia ◽  
Ecosystem Respiration ◽  
Block Design ◽  
Net Ecosystem Exchange ◽  
Carbon Exchange ◽  
Ecosystem Productivity ◽  
Temperature And Precipitation ◽  
Gross Ecosystem Productivity

Aspects of carbon exchange were investigated in typical steppe east of Xilinhot city in Inner Mongolia. Four treatments with four replicates were imposed in a randomised block design: Control (C), warming (T), increased precipitation (P) and combined warming and increased precipitation (TP). Increased precipitation significantly increased both ecosystem respiration (ER) and soil respiration (SR) rates. Warming significantly reduced the ER rate but not the SR rate. The combination of increased precipitation and warming produced an intermediate response. The sensitivity of ER and SR to soil temperature and air temperature was assessed by calculating Q10 values: the increase in respiration for a 10°C increase in temperature. Q10 was lowest under T and TP, and highest under P. Both ER and SR all had significantly positive correlation with soil moisture. Increased precipitation increased net ecosystem exchange and gross ecosystem productivity, whereas warming reduced them. The combination of warming and increased precipitation had an intermediate effect. Both net ecosystem exchange and gross ecosystem productivity were positively related to soil moisture and negatively related to soil and air temperature. These findings suggest that predicted climate change in this region, involving both increased precipitation and warmer temperatures, will increase the net ecosystem exchange in the Stipa steppe meaning that the ecosystem will fix more carbon.

scholarly journals Pan-Arctic linkages between snow accumulation and growing-season air temperature, soil moisture and vegetation

2013 ◽  
Vol 10 (11) ◽  
pp. 7575-7597 ◽  
Author(s):  
K. A. Luus ◽  
Y. Gel ◽  
J. C. Lin ◽  
R. E. J. Kelly ◽  
C. R. Duguay
Keyword(s):  
Soil Moisture ◽  
Air Temperature ◽  
Land Surface ◽  
Regional Scale ◽  
Surface Characteristics ◽  
Growing Season ◽  
Snow Accumulation ◽  
Snow Season ◽  
Air Temperatures ◽  
Land Surface Characteristics

Abstract. Arctic field studies have indicated that the air temperature, soil moisture and vegetation at a site influence the quantity of snow accumulated, and that snow accumulation can alter growing-season soil moisture and vegetation. Climate change is predicted to bring about warmer air temperatures, greater snow accumulation and northward movements of the shrub and tree lines. Understanding the responses of northern environments to changes in snow and growing-season land surface characteristics requires: (1) insights into the present-day linkages between snow and growing-season land surface characteristics; and (2) the ability to continue to monitor these associations over time across the vast pan-Arctic. The objective of this study was therefore to examine the pan-Arctic (north of 60° N) linkages between two temporally distinct data products created from AMSR-E satellite passive microwave observations: GlobSnow snow water equivalent (SWE), and NTSG growing-season AMSR-E Land Parameters (air temperature, soil moisture and vegetation transmissivity). Due to the complex and interconnected nature of processes determining snow and growing-season land surface characteristics, these associations were analyzed using the modern nonparametric technique of alternating conditional expectations (ACE), as this approach does not impose a predefined analytic form. Findings indicate that regions with lower vegetation transmissivity (more biomass) at the start and end of the growing season tend to accumulate less snow at the start and end of the snow season, possibly due to interception and sublimation. Warmer air temperatures at the start and end of the growing season were associated with diminished snow accumulation at the start and end of the snow season. High latitude sites with warmer mean annual growing-season temperatures tended to accumulate more snow, probably due to the greater availability of water vapor for snow season precipitation at warmer locations. Regions with drier soils preceding snow onset tended to accumulate greater quantities of snow, likely because drier soils freeze faster and more thoroughly than wetter soils. Understanding and continuing to monitor these linkages at the regional scale using the ACE approach can allow insights to be gained into the complex response of Arctic ecosystems to climate-driven shifts in air temperature, vegetation, soil moisture and snow accumulation.

scholarly journals Modeling the contributions of global air temperature, synoptic-scale phenomena and soil moisture to near-surface static energy variability using artificial neural networks

2017 ◽  
Author(s):  
Sara C. Pryor ◽  
Ryan C. Sullivan ◽  
Justin T. Schoof
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Soil Moisture ◽  
Air Temperature ◽  
Energy Content ◽  
Daily Maximum ◽  
Synoptic Scale ◽  
Near Surface ◽  
Artificial Neural ◽  
Static Energy

Abstract. The static energy content of the atmosphere is increasing at the global scale, but exhibits important sub-global and sub-regional scales of variability and is a useful parameter for integrating the net effect of changes in the partitioning of energy at the surface and for improving understanding of the causes of so-called warming-holes (i.e. locations with decreasing daily maximum air temperatures (T) or increasing trends of lower magnitude than the global mean). Further, measures of the static energy content (herein the equivalent potential temperature, θe) are more strongly linked to excess human mortality and morbidity than air temperature alone, and have great relevance in understanding causes of past heat-related excess mortality and making projections of possible future events that are likely to be associated with negative human health and economic consequences. A new non-linear statistical model for summertime daily maximum and minimum θe is developed and used to advance understanding of drivers of historical change and variability over the eastern USA. It is shown that soil moisture (SM) is particularly important in determining the magnitude of θe over regions that have previously been identified as exhibiting warming holes confirming the key importance of SM in dictating the partitioning of net radiation into sensible and latent heat and dictating trends in near-surface T and θe. Consistent with our a priori expectations, models built using Artificial Neural Networks (ANN) out-perform linear models that do not permit interaction of the predictor variables (global T, synoptic-scale meteorological conditions and SM). This is particularly marked in regions with high variability in min- and max-θe, where more complex models built using ANN with multiple hidden layers are better able to capture the day-to-day variability in θe and the occurrence of extreme max-θe. Over the entire domain the ANN with 3 hidden layers exhibits high accuracy in predicting max-θe > 347 K. The median hit rate for max-θe > 347 K is > 0.60, while the median false alarm rate ≈ 0.08.

scholarly journals Influência de Mudanças Climáticas no Balanço Hídrico da Amazônia Ocidental (Influence of Climate Change on Water Budget of Western Amazonia)

2011 ◽  
Vol 3 (3) ◽  
pp. 170 ◽  
Author(s):  
Ailton Marcolino Liberato ◽  
José Ivaldo B. De Brito
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Air Temperature ◽  
Water Budget ◽  
Fire Risk ◽  
Climate Index ◽  
Climate Trends ◽  
Climatological Data ◽  
Temperature And Precipitation

A presente pesquisa teve por objetivo investigar possíveis alterações em componentes do balanço hídrico climático, associadas a diferentes cenários (A2 e B2) das mudanças climáticas do IPCC, para a Amazônia Ocidental (Acre, Amazonas, Rondônia e Roraima). Os dados climatológicos de temperatura do ar e totais de precipitação pluvial usados como referência neste estudo, são oriundos do INMET (1961-2005), da CEPLAC (1983-1999) e da reanálise do NCEP/NCAR (1983-1995). O método utilizado na elaboração do balanço hídrico é o de Thornthwaite e Mather (1957) modificado por Krishan (1980). Os resultados das projeções mostram tendência de clima mais seco, diminuição na umidade do solo, redução na vazão dos rios, aumento no risco de incêndio e diminuição no escoamento superficial e sub-superficial para a Amazônia Ocidental até 2100.Palavras-chave: cenários, índices climáticos, Amazônia. Influence of Climate Change on Water Budget of Western Amazonia ABSTRACTThe main objective of this study was investigate possible alterations in the climatic water budget components associated with different scenarios (A2 and B2) of the IPCC to Amazonian Western (Acre, Amazonas, Rondônia and Roraima). The climatological data of air temperature and precipitation from the INMET (1961-2005), CEPLAC (1983-1999) and NCEP/NCAR reanalysis (1983-1995) were used in the present study. The Thornthwaite and Mather (1955) method was used in the elaboration of the climatic water budget modified by Krishan (1980). The results of the projections show drier climate trends and decrease of the soil moisture, reduction in the rivers discharge, increase in the fire risk and decrease in the runoff for the Amazonian Western up to 2100. Keywords: scenarios, climate index, Amazonian.

scholarly journals Prototype Alat Penyiram Tanaman Otomatis dengan Sensor Kelembaban dan Suhu Berbasis Arduino

2020 ◽  
Vol 1 (1) ◽  
pp. 21-25
Author(s):  
Shamaratul Fuadi ◽  
Oriza Candra
Keyword(s):  
Soil Moisture ◽  
Air Temperature ◽  
Water Discharge ◽  
Sensor Data ◽  
Water Pump ◽  
Final Project ◽  
Plant Soil ◽  
Control Water

Quality plants are produced by observing soil moisture and plant temperature. Plants humidity and temperature are affected by plant irrigations system. Therefore, this Final Project aims to make a plant sprinklers that can control water discharge according to plant needs. Using the Soilmoisture Sensor which functions as a reader of plant soil moisture and DHT11 as a reader of the air temperature around the plant. Then the relay module functions to activate and deactivate the water pump. LCD is used to display the  data results and the ESP8266 Module is also used as a display of the results of sensor data, which will be sent to the thingspeak.com website

scholarly journals On the Estimation of Soil Moisture using Precipitation and Air Temperature

1968 ◽  
Vol 20 (1) ◽  
pp. 51-51
Author(s):  
Yoshitaka FUKUOKA
Keyword(s):  
Soil Moisture ◽  
Air Temperature

scholarly journals Soil temperature study in Puerto Rico

1969 ◽  
Vol 93 (3-4) ◽  
pp. 149-171
Author(s):  
Jorge L. Lugo-Camacho ◽  
Miguel A. Muñoz ◽  
Juan Pérez-Bolívar ◽  
Gregory R. Brannon
Keyword(s):  
Puerto Rico ◽  
Soil Moisture ◽  
Soil Temperature ◽  
Sea Level ◽  
Air Temperature ◽  
Temperature Regime ◽  
Soil Series ◽  
Soil Temperature Regime ◽  
The Mean ◽  
Mean Annual Air Temperature

Soil temperature measurements from a climate monitoring network in Puerto Rico were evaluated and the difference between mean summer and mean winter soil temperature, known as isotivity value, was calculated. Air and soil temperature was collected from five weather stations of the USDA-Natural Resources Conservation Service from sea level to 1,019 m above sea level and from different soil moisture regimes. Isotivity values ranged from 1.2 to 3.9° C with an average of 2.6° C. The 750-m elevation was identified as the limit between the isohyperthermic and isothermic soil temperature regimes in the perudic soil moisture regime in Puerto Rico. The greatest differences between mean annual soil temperature and mean annual air temperature were observed at Guánica, Combate and Guilarte (2.1 ° C) stations. The smallest differences were observed at Maricao (0.8° C) and Isabela (1.8° C) stations. The study also indicated that the mean annual soil temperature in Puerto Rico can be estimated by adding 1.8° C to the mean annual air temperature or by the equation y = -0.007x + 28.0° C. The equation indicates that 97 percent of the time the behavior of the mean annual soil temperature is a function of elevation. According to the updated soil temperature regime boundaries, eight soil series were established in the Soil Survey of San Germán Area. In an area under the isothermic soil temperature regime, four soil series were classified as Oxisols (Haploperox), two soil series as Inceptisols (Eutrudepts) and two soil series as Mollisols (Argiudolls). This is the first field recognition of the Haploperox soil great group in the United States and its territories.

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