CN103761446A - Method for estimating global mean temperature and regional mean temperature through MODIS temperature product - Google Patents
Method for estimating global mean temperature and regional mean temperature through MODIS temperature product Download PDFInfo
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Abstract
The invention relates to a method for estimating a global mean temperature and a regional mean temperature through an MODIS temperature product. The method can be applied to meteorology, environment monitoring, land management, agricultural condition monitoring, disaster monitoring and other remote sensing application fields. The method comprises five steps: in the first step, space mean temperatures at different moments t (1:30, 10:30, 13:30 and 22:30) are calculated through an MODIS mean monthly temperature product; in the second step, the global mean temperature at the moments t is calculated; in the third step, information calculated in the first step and information calculated in the second step are utilized for calculating the daily mean maximum value and the daily mean minimum value; in the fourth step, data at six time points in the whole day are subjected to unary repeated fitting to obtain a mean temperature variation curve chart and mean temperature calculation formula coefficients, and the global mean temperature is calculated.
Description
Technical field
The present invention relates to a kind of method of utilizing MODIS surface temperature product on earth observation satellite to calculate the whole world and zone leveling surface temperature, broken through the limitation that classic method is utilized meteorological observation.Can be applied in the remote sensing departments such as meteorology, agricultural, environmental monitoring and Monitoring of drought.
Background technology
In this method, the whole world and zone leveling temperature refer to the whole world and zone leveling every day and temperature hourly, and it is a very important parameter in climate change research.Because global medial temperature is subject to time and space, and the impact of earth's surface situation, also do not have so far a kind of method can estimate well global medial temperature.At present, it is known in climate change research that to obtain global medial temperature be mainly a kind of method, utilize meteorological site to carry out spatial interpolation, then utilize area weight to calculate [Hansen, J. E. et al. Global climate changes as forecast by Goddard Institute for space studies three-dimensional model, Journal of geophysical research, 93 (D8), 9341-9364 (1988), Boyer, D. G., Estimation of daily temperature means using elevation and latitude in mountainous terrain, Water Resource Bull 4,583-5889 (1984), Hansen, J.E. and Lebedeff, S. Global trends of measured surface air temperature. J. Geophys. Res., 92,13345-13372, (1987), Hansen, J. E. et al. Global climate changes as forecast by Goddard Institute for space studies three-dimensional model, Journal of geophysical research, 93 (D8), 9341-9364 (1988). Hansen, J., Ruedy, R., Glascoe, J. and M. Sato, GISS analysis of surface temperature change, J. Geophys. Res., 104, 30, 997 – 31, 022, (1999). Hansen, J. E. et al. A closer look at United States and global surface temperature change. J. Geophys. Res., 106, 23947-23963, (2001). Fan, Y., Dool, H.V.D., A global monthly land surface air temperature analysis for 1948 – present, Journal of Geophysical Research, 113 (D01103), 1-18, (2008) .].Meteorological site limited amount; and be not uniformly distributed; particularly at mountain area and utmost point low country; the result that interpolation obtains is not very good; precision is not very high, so people carry out temperature anomaly analysis and research [Hansen, J. et al. Global temperature change. Proc. Natl. Acad. Sci. 103 more; 14288-14293, (2006); Hansen, J., Sato M., Ruedy R., Perception of climate change, PNAS 6,2415 – 2423, (2012) .].
MODIS remote sensor carried earth observation satellite successful launch in 1999 and 2002, for global and region resource environmental dynamic monitor have been opened up another new approach.MODIS is an intermediate-resolution remote sensing system that has 36 wave bands, can obtain 4 global observation data (1:30,10:30,13:30,22:3) every day, its flight and sun synchronization, and be free reception, be therefore applicable to very much global temperatures monitoring.In 36 wave bands of MODIS, there are 8 to be thermal infrared wave band, thus most suitable in the Ground Heat quantity space variance analysis of regional scale.At present for the Surface Temperature Retrieval algorithm of MODIS remotely-sensed data many [Wan, Z. M. and Li, Z. L., A physics-based algorithm for retrieving land-surface emissivity and temperature from EOS/MODIS data. IEEE Transactions on Geoscience and Remote Sensing, 1997,35 (4): 980-996, Mao Kebiao, for the Surface Temperature Retrieval method research of MODIS data, master thesis, Nanjing University, 2004.5., Mao Kebiao, Qin Zhihao, execute and build up, palace roc, for MODIS data, split window algorithm research, Wuhan University Journal (information science version), 2005(8): 703-708.], NASA (NASA) provides the global temperatures moon product of 4 times every day, its Product Precision is also very high [Otis B. Brown Peter J. Minnett With contributions from:R. Evans, E. Kearns, K. Kilpatrick, A. Kumar, R. Sikorski & A. Z á vody, MODIS Infrared Sea Surface Temperature Algorithm Algorithm Theoretical Basis Document (SST ATBD) Version 2, University of Miami, Miami, FL 33149-1098 (1999)., Wan, Z. M., MODIS Land-Surface Temperature Algorithm Theoretical Basis Document (LST ATBD) Version 3.3, Institute for Computational Earth System Science, University of California, Santa Barbara, CA. (1999) .].Also do not utilize at present the method for the MODIS surface temperature product estimation whole world and zone leveling temperature to deliver.
Summary of the invention
The object of the present invention is to provide a kind of from the remotely-sensed data MODIS temperature product estimation whole world and zone leveling temperature methods, the practical difficulty that utilizes meteorological site to calculate to overcome existing surface temperature, and meteorological site interpolation is difficult to guarantee the shortcoming of precision, further improve the estimation precision of global energy equilibrium model.
For achieving the above object, the method from the remotely-sensed data MODIS temperature product estimation whole world and zone leveling temperature provided by the invention is:
The first step: raw data is processed and space interpolation processing, then calculated the space average temperature of different time t (1:30,10:30,13:30,22:30) with equation 1 from MODIS monthly mean temperature product.
In formula
it is pixel
in the medial temperature of time t,
it is the number of days in a year.
Second step: equation 2 calculates t whole world medial temperature constantly
In formula
moment t medial temperature,
number of days every day,
pixel number,
pixel j area weight function,
it is time t (1:30,10:30,13:30,22:30) temperature.
The 3rd step: the information of utilizing the first step and second step to calculate is calculated maximal value and the minimum value of average every day.Equation 3 is used to the medial temperature information in 4 moment of approximate treatment.
In formula
it is medial temperature.Utilize 4 constantly data calculate, calculate average every day of maximal value and minimum value, basicly stable in the temperature of 4 moment point (1:30,10:30,13:30,22:30) every year.Suppose that every day, medial temperature minimumly occurred in morning 3, maximum temperature is 3 points in the afternoon, and it is just profound curvilinear motion that local temperature changes.Meet formula 4 and 5.Utilize formula 4 and moment 10:30 and 13:30 data point, calculate maximum temperature.Utilize equation 5 and moment 22:30 and 1:30 data, calculate average minimum.
(5)
A in formula, B parameter can calculate by calculating the data substitution of 4 points.
The 4th step: utilize the data of 6 points of whole day to carry out repeatedly matching of monobasic, obtain medial temperature change curve and equation 6 and 7.Calculate global medial temperature.
A in formula, b, the parameters such as c can obtain by matching.Equation 6 and 7 can be used for obtaining average every day of medial temperature hourly.The equation that calculates the average temperature in the whole world is formula 8.
The invention has the beneficial effects as follows, utilize the temperature of MODIS surface temperature product different time every day, by constructing the whole world and region medial temperature every day change curve, calculate the medial temperature in the whole world and region, effectively overcome classic method meteorological site lazy weight in the past, skewness, and proofread and correct inconsistent shortcoming.For climate change research, weather forecast, evapotranspiration, the monitoring of agriculture feelings and disaster monitoring etc. provide effective means and technical support.Its operation practicality must be simple than traditional Ground Meteorological observation station point interpolation that utilizes, and on face, precision wants high.In fact, surface weather observation station is also that this method is further carried high-precision data important supplement source, and the two is in conjunction with will greatly improving the estimation precision of global medial temperature.
Accompanying drawing explanation
Below in conjunction with drawings and Examples, the present invention is further described.
Accompanying drawing explanation
Fig. 1 is that global temperatures in 2012 is at 4 time points (1:30,10:30,13:30,22:30) medial temperature distribution plan.
Fig. 2 is 4 time points whole world medial temperatures in 2001 to 2012 and the highlyest distributes with minimum temperature.
Fig. 3 is the matched curve of global 200d 1-2012 annual temperature variation every day.
Embodiment
An example that calculates calendar year 2001 to 2012 year global medial temperature calculating is provided here:
This example is realized (method) and is mainly comprised four steps:
The first step: raw data is carried out to interpolation processing, and we calculate the space average temperature of different time t (1:30,10:30,13:30,22:30) from MODIS monthly mean temperature product with equation 1.Fig. 1 is that we calculate 2008 at 4 time points every day (1:30,10:30,13:30,22:30) space average temperature profile.
Second step: equation 2 calculates t whole world medial temperature constantly.
The 3rd step: the information of utilizing the first step and second step to calculate is calculated maximal value and the minimum value of average every day.Equation 3 is used to the medial temperature information in 4 moment of approximate treatment.Global 200d 1 year to 2012 in time t (1:30,10:30,13:30,22:30) medial temperature result of calculation as table 1.
Table 1 2001 to 2012 is in medial temperature in the same time not
Calculate average every day of maximal value and minimum value, Fig. 2 a, b, c, d is 4 data points constantly in table 2, as can be seen from the figure, basicly stable in the temperature of 4 moment point (1:30,10:30,13:30,22:30) every year.Suppose the minimum 3:00 AM that occurs in of medial temperature every day, maximum temperature is 3 points in the afternoon, and it is just profound curvilinear motion that local temperature changes.Meet formula 4 and 5.Utilize formula 4 and a, b 2 points, calculate 16.941 ° of C of maximum temperature.Utilize equation 5 and some c, d, calculates 12.239 ° of C of average minimum.
The 4th step: Fig. 1 is carried out to repeatedly matching of monobasic, obtain medial temperature change curve Fig. 3 and equation 6 and 7.Equation 6 and 7 can be used for obtaining average every day of medial temperature hourly.The equation that calculates the average temperature in the whole world is formula 8.Table 1 is the medial temperature of calculating, and nearly 12 years (2001 to the 2012) medial temperatures in the whole world are 14.53 ° of C.Comparison sheet 1 and table 2 data, can find, the medial temperature that the global medial temperature that equation 3 calculates and equation 8 calculate only differs 0.07 ° of C, so in the situation that requiring not to be very high, also can approximate treatment whole world medial temperature with equation 3.
The average medial temperature per hour every day (formula 8) of table 2
Claims (2)
1. from the MODIS temperature product estimation whole world and zone leveling temperature methods
,the steps include: the first step: we calculate the space average temperature of different time t (1:30,10:30,13:30,22:30) from MODIS monthly mean temperature product; Second step: calculate t whole world medial temperature constantly; The 3rd step: the information of utilizing the first step and second step to calculate is calculated maximal value and the minimum value of average every day, calculates the medial temperature information in 4 moment; Utilize 4 constantly data calculate average every day of maximal value and minimum value; Obtain the time that the whole world or region reach minimum and maximum temperature, determine that every day, medial temperature minimumly occurred in the time in morning, maximum temperature is in the time, and it is just profound curvilinear motion that local temperature changes; Matched curve equation also calculates the highest and minimum temperature; The 4th step: utilize the data of six points of whole day to carry out repeatedly matching of monobasic, obtain medial temperature change curve and equation, calculate the average temperature in the whole world, finally calculate medial temperature.
2. according to requirement in right 1, from the MODIS temperature product estimation whole world and the common feature of zone leveling temperature methods, be generally by 4 temperature in the satellite acquisition whole world, set up local function and determine minimum and maximum value, last matching whole day temperature variation curve, calculates whole day medial temperature.
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| CN105095628A (en) * | 2014-05-16 | 2015-11-25 | 中国农业科学院农业资源与农业区划研究所 | Method for monitoring spatial-temporal change of global vegetation coverage |
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| CN108629107A (en) * | 2018-04-28 | 2018-10-09 | 中国水利水电科学研究院 | A kind of method and device calculating degree/day |
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