CN106777963A - A kind of method that accumulated temperature and accumulated temperature number of days are obtained based on moon samming - Google Patents
A kind of method that accumulated temperature and accumulated temperature number of days are obtained based on moon samming Download PDFInfo
- Publication number
- CN106777963A CN106777963A CN201611146491.6A CN201611146491A CN106777963A CN 106777963 A CN106777963 A CN 106777963A CN 201611146491 A CN201611146491 A CN 201611146491A CN 106777963 A CN106777963 A CN 106777963A
- Authority
- CN
- China
- Prior art keywords
- accumulated temperature
- samming
- moon
- days
- day
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16Z—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS, NOT OTHERWISE PROVIDED FOR
- G16Z99/00—Subject matter not provided for in other main groups of this subclass
Abstract
The invention discloses a kind of method for obtaining accumulated temperature and accumulated temperature number of days based on moon samming, the method comprises the following steps：The day samming data of target area are collected, the accumulated temperature in all times where calculating day samming data starts day, accumulated temperature closing day；Make its accumulated temperature start earliest moon day for first effective moon, make its accumulated temperature closing day moon the latest for last effective moon；Judge the first corresponding relation between accumulated temperature and moon samming, judge the second corresponding relation between accumulated temperature number of days, moon samming and accumulated temperature；The moon samming data of target area all the time samming data period are collected, using the first corresponding relation and the second corresponding relation, by moon samming data acquisition target area all the time accumulated temperature of samming data period and accumulated temperature number of days.The present invention innovatively using the existing accumulated temperature and accumulated temperature number of days that the correspondence time is obtained to accumulated temperature and the effective moon samming data of accumulated temperature number of days, has the advantages that method is simple, accuracy is high, highly reliable.
Description
Technical field
The present invention relates to climatic elements computational methods technical field, specifically for, the present invention is a kind of based on monthly
The method that temperature obtains accumulated temperature and accumulated temperature number of days.
Background technology
Obtainable heat resources and its duration decide the vital movement of biology in certain area.Heat resources is believed
Breath is generally represented by accumulated temperature GDD [DEG C d] and accumulated temperature number of days GS [d], is the finger of the influence quantification by temperature to vegetation growth
Mark.
The definition of GS is the number of days that a certain temperature threshold Tb [DEG C] is continued to exceed in a year, and temperature threshold Tb is usually 0,5
Or 10 DEG C；GDD exceedes the aggregate-value of the temperature section of threshold value during being then GS：Beginning day and the closing day of accumulated temperature are first calculated, is opened
The number of days begun between day and closing day is GS, and then calculates GDD.That is, traditional computational methods must be by day
Samming data calculate the accumulated temperature and accumulated temperature number of days in corresponding time.
But, meteorological site is sparse before nineteen fifty, day samming information very little, it is impossible in aforementioned manners calculate GDD and
GS。
Therefore, the accumulated temperature in its correspondence time how is calculated in the case of day few samming data even without day of samming data
With accumulated temperature number of days, those skilled in the art's technical problem urgently to be resolved hurrily and the emphasis studied all the time are had become.
The content of the invention
To solve the problems, such as that existing method cannot calculate the accumulated temperature and accumulated temperature number of days in day samming data few time, the present invention
A kind of method that accumulated temperature and accumulated temperature number of days are obtained based on moon samming is disclosed, from the angle of moon samming, day is thoroughly solved
The accumulated temperature and the computational problem of accumulated temperature number of days in its correspondence time in the case of the few samming data even without day of samming data.
To realize above-mentioned technical purpose, the invention discloses a kind of side that accumulated temperature and accumulated temperature number of days are obtained based on moon samming
Method, the method comprises the following steps,
Step 1, collects the day samming data of target area, the product in all times where calculating it by day samming data
Temperature starts day, accumulated temperature closing day；
Step 2, for all times where day samming data, makes its accumulated temperature start earliest moon day for first effectively
Month, it is last effective moon to make its accumulated temperature closing day moon the latest；
Step 3, all times where calculating day samming data are between first effective moon and last effective moon
Accumulated temperature actual value, moon samming and accumulated temperature number of days actual value, judge the first corresponding relation between accumulated temperature and moon samming, judge product
The second corresponding relation between warm number of days, moon samming and accumulated temperature；
Step 4, collects the moon samming data of target area all the time samming data period, using first corresponding relation and
Second corresponding relation, by moon samming data acquisition target area all the time accumulated temperature of samming data period and accumulated temperature number of days.
Compared with prior art, the present invention is extracted to accumulated temperature and the effective moon samming of accumulated temperature number of days, makes evaluation method
It is simpler and more meet logic；In addition, the present invention estimate accumulated temperature number of days when, in addition to effective month samming, also use accumulated temperature and
The relation of accumulated temperature number of days, by being found after comparison test, the present invention can accurately extract caloric information.Therefore, the present invention is thoroughly solved
Determine and calculated in the case of day few samming data even without day of samming data the accumulated temperature and accumulated temperature number of days in its correspondence time
Problem.
Further, in step 3, judge that between accumulated temperature and moon samming first corresponding closes using multiple linear regression analysis method
System, i.e. accumulated temperature estimation equation：Determine aiWith the value of c；
Wherein, GDD is accumulated temperature, and mo is first effective moon, and me is last effective moon, Tm,iIt is monthly for i-th month
Temperature, aiIt is parameter, c is constant.
Further, in step 3, using multiple linear regression analysis method judge accumulated temperature number of days, moon samming and accumulated temperature it
Between the second corresponding relation, i.e. accumulated temperature number of days estimation equation：
Determine bi, d and e value；
Wherein, GS is accumulated temperature number of days, and GDD is accumulated temperature, and mo is first effective moon, and me is last effective moon, Tm,iFor
The moon samming of i-th month, biWith d parameters, e is constant.
Further, the accuracy and reasonability of scheme to illustrate the invention, in step 3, calculating has day samming number
According to place time effective moon samming, the first corresponding relation is verified using the effectively monthly gentle accumulated temperature actual value, using described
Effective moon samming, accumulated temperature actual value, accumulated temperature number of days verify the second corresponding relation.
Further, in step 3, for the effective monthly gentle accumulated temperature actual value place time and the institute in step 1 that verify
State all times different.By the checking of other time data, accuracy of the invention is further illustrated.
Further, in step 3, the first corresponding relation is verified using mean absolute error, average deviation, root-mean-square error
With the simulation effect of the second corresponding relation.
Further, in step 3, the simulation effect includes numerical values recited and Annual variations.
Further, in step 3, all times where calculating day samming data using method average month by month are first
Moon samming between individual effective moon and last effective moon.
Further, in step 1, the accumulated temperature in all times where calculating day samming data using moving average method on the five
Start day, accumulated temperature closing day.
Further, in step 1, the target area is the region observed all the year round in observation website.
Beneficial effects of the present invention are：The present invention is innovatively using existing effective monthly to accumulated temperature and accumulated temperature number of days
Warm data obtain the accumulated temperature and accumulated temperature number of days in correspondence time, have the advantages that method is simple, accuracy is high, highly reliable.Pass through
Comparison test finds that the present invention can accurately extract caloric information.
Brief description of the drawings
Fig. 1 is the method flow schematic diagram that the present invention obtains accumulated temperature and accumulated temperature number of days based on moon samming.
Specific embodiment
The method for obtaining accumulated temperature and accumulated temperature number of days based on moon samming of the invention is carried out in detail with reference to Figure of description
Thin explanation and explanation.
As shown in figure 1, the invention discloses a kind of method for obtaining accumulated temperature GDD and accumulated temperature number of days GS based on moon samming, profit
The relation of moon samming data and accumulated temperature, moon samming data and accumulated temperature and accumulated temperature number of days is extrapolated with existing day samming data, it is right
There is a moon time for samming data in all the time samming data, all the time accumulated temperature in samming time and accumulated temperature day are drawn according to above-mentioned relation
Number.The method comprises the following steps：
Step 1, the website observe all the year round certain collected the day samming T in some times of target areadData, GDD and GS
Mainly started to be influenceed day and every other day Close Date samming by GS, the present invention calculate it by day samming data where all years
The accumulated temperature of part starts day, accumulated temperature closing day；In the present invention, using all where moving average method calculating day samming data on the five
The accumulated temperature in time starts day, accumulated temperature closing day, and target area is the region observed all the year round in observation website.
In the present embodiment, the day samming data of 1960-2011 are collected.545 meteorological sites of Chinese 1960-2011
Homogenization day samming data, the data set is because having carried out homogenization treatment, and the reliability than source data is higher, can be used for weather change
Change research.Website on the lofty high mountain of flat country, because the climatic environment that their data can not represent peripheral region is special
Levy, do not consider.Finally, 536 data of website will be used to calculate.
Step 2, according to the data of 1960-2010, for all times where day samming data, makes its accumulated temperature start
Day earliest moon is first effective moon, makes its accumulated temperature closing day moon the latest for last effective moon.
The conventional temperature threshold of Chinese accumulated temperature is typically 0,5 and 10 DEG C, because number of days and plant more than 10 DEG C are most quick
The duration of growth is suitable, therefore, 10 DEG C are selected in the present embodiment as threshold calculations GDD (DEG C d) and GS (d).
Step 3, the data based on 1960-2010, all times where calculating day samming data are effective at first
Month and the accumulated temperature actual value between last effective moon, moon samming and accumulated temperature number of days actual value, judge accumulated temperature and the moon samming it
Between the first corresponding relation, judge the second corresponding relation between accumulated temperature number of days, moon samming and accumulated temperature；In the present embodiment, utilize
All times where method calculating day samming data average month by month are between first effective moon and last effective moon
Moon samming Tm。
For the first corresponding relation, judge that between accumulated temperature and moon samming first corresponding closes using multiple linear regression analysis method
System, i.e. accumulated temperature estimation equation：The present invention determines a with multiple linear regression analysis methodiWith the value of c；
Goodness of fit R2Up to 0.90 ± 0.09, and passed through significance test, wherein, conspicuousness p value<0.001, illustrate equation can
It is very high by property.
Wherein, GDD is accumulated temperature, and mo is first effective moon, and me is last effective moon, Tm,iIt is monthly for i-th month
Temperature, aiIt is parameter, c is constant.
For the second corresponding relation, using multiple linear regression analysis method judge accumulated temperature number of days, moon samming and accumulated temperature it
Between the second corresponding relation, i.e. accumulated temperature number of days estimation equation：
Determine bi, d and e value；Goodness of fit R2Up to 0.73 ± 0.10, and lead to
Significance test has been crossed, wherein, conspicuousness p value<0.001, illustrate that the reliability of equation is very high.
Wherein, GS is accumulated temperature number of days, and GDD is accumulated temperature, and mo is first effective moon, and me is last effective moon, Tm,iFor
The moon samming of i-th month, biWith d parameters, e is constant.
The present invention is verified to above-mentioned accumulated temperature estimation equation and accumulated temperature number of days estimation equation, to illustrate its correctness.
Specifically, calculating has time effective moon samming where day samming data, using effectively monthly gentle accumulated temperature actual value checking the
One corresponding relation, the effective moon that will obtain accumulated temperature actual value substitutes into accumulated temperature estimation equation, and the accumulated temperature for calculating is true with accumulated temperature
Value is compared；The second corresponding relation is verified using effective month samming, accumulated temperature actual value, accumulated temperature number of days, accumulated temperature number of days will have been obtained true
Real-valued effective moon and the accumulated temperature for estimating substitute into accumulated temperature number of days estimation equation, and the accumulated temperature number of days for calculating is true with accumulated temperature number of days
Value is compared.To further illustrate the reasonability of its checking, the present invention is for where the effective monthly gentle accumulated temperature actual value of checking
Time is different from all times described in step 1, such as, (1) be not used for modeling the day with 536 websites in 2011 be number
According to directly calculating GDD and GS：It is observation to be denoted by, and calculates a moon samming data, and substituting into above-mentioned equation can simulate GDD
And GS, it is designated as s-site；(2) lattice point month samming data in 2011, according to lattice point geographic location correspondence website, in substitution
GDD and GS is simulated by stating equation, s-cru is designated as.By contrast, can analysis s-site and s-cru truly reflect observation
Value.In the present embodiment, using mean absolute error MAE (mean absolute error), average deviation MBE (mean bias
Error), root-mean-square error RMSE (root mean square error) verifies the first corresponding relation and the second corresponding relation
Simulation effect, simulation effect includes numerical values recited and Annual variations.Found by contrasting, although s-cru errors are than s-site's
Greatly, the distribution characteristics of observation and the size of value but can also be reflected.By comparing result, our this use moon samming data
The accuracy of the method for GDD and GS is simulated, one is influenceed by model performance, its error for showing as s-site, two is by monthly
The accuracy influence of warm data.Wherein, the error very little that model performance brings, this programme reliability is ensured.
Step 4, collects the moon samming data of target area all the time samming data period, that is, extract local all the time samming observation
The caloric information in value period, recycles the first corresponding relation and the second corresponding relation, by moon samming data acquisition target area
The all the time accumulated temperature of samming data period and accumulated temperature number of days.
In the present embodiment, collect target area 1901-2011 days samming data, using the present invention available 1901 to
1959 accumulated temperature and accumulated temperature number of days.By global climatological observation value interpolation, resolution ratio is 0.5 ° × 0.5 ° longitude and latitude to the data
Degree, for climate change research.Choosing the data of the lattice point (0.5 ° × 0.5 °) on geographical position comprising website is used to calculate,
Finally, 536 lattice points are picked out.The moon samming data of the 536 CRU lattice points 1901-2010 that will be selected, according to where lattice point
Geographical position correspondence website, is updated in GDD models and GS models, draws the GDD and GS of Chinese 1901-2010.
In the description of this specification, reference term " one embodiment ", " some embodiments ", " the present embodiment ", " specific
The description of example " or " some examples " etc. mean to combine the specific features that the embodiment or example describe, structure, material or
Feature is contained at least one embodiment of the invention or example.In this manual, to the schematic representation of above-mentioned term
Necessarily it is directed to identical embodiment or example.And, the specific features of description, structure, material or feature can be
Combined in an appropriate manner in any one or more embodiments or example.Additionally, in the case of not conflicting, this area
Technical staff can be carried out the feature of the different embodiments or example described in this specification and different embodiments or example
With reference to and combination.
Presently preferred embodiments of the present invention is these are only, is not intended to limit the invention, it is all in substance of the present invention
On any modification, equivalent and the simple modifications made etc., should be included within the scope of the present invention.
Claims (10)
1. a kind of method that accumulated temperature and accumulated temperature number of days are obtained based on moon samming, it is characterised in that：The method comprises the following steps,
Step 1, collects the day samming data of target area, and the accumulated temperature in all times where calculating it by day samming data is opened
Begin day, accumulated temperature closing day；
Step 2, for all times where day samming data, it is first effective moon to make its accumulated temperature start earliest moon day,
It is last effective moon to make its accumulated temperature closing day moon the latest；
Step 3, the product of all times where calculating day samming data between first effective moon and last effective moon
Warm actual value, moon samming and accumulated temperature number of days actual value, judge the first corresponding relation between accumulated temperature and moon samming, judge accumulated temperature day
Number, the second corresponding relation between moon samming and accumulated temperature；
Step 4, collects the moon samming data of target area all the time samming data period, using first corresponding relation and second
Corresponding relation, by moon samming data acquisition target area all the time accumulated temperature of samming data period and accumulated temperature number of days.
2. the method that accumulated temperature and accumulated temperature number of days are obtained based on moon samming according to claim 1, it is characterised in that：Step 3
In, the first corresponding relation between judging accumulated temperature and moon samming using multiple linear regression analysis method, i.e. accumulated temperature estimation equation：Determine aiWith the value of c；
Wherein, GDD is accumulated temperature, and mo is first effective moon, and me is last effective moon, Tm,iIt is the moon samming of i-th month, ai
It is parameter, c is constant.
3. the method that accumulated temperature and accumulated temperature number of days are obtained based on moon samming according to claim 1, it is characterised in that：Step 3
In, judge the second corresponding relation between accumulated temperature number of days, moon samming and accumulated temperature, i.e. accumulated temperature using multiple linear regression analysis method
Number of days estimation equation：
Determine bi, d and e value；
Wherein, GS is accumulated temperature number of days, and GDD is accumulated temperature, and mo is first effective moon, and me is last effective moon, Tm,iIt is i-th
The moon samming of individual month, biWith d parameters, e is constant.
4. the method that accumulated temperature and accumulated temperature number of days are obtained based on moon samming according to claim 1,2 or 3, it is characterised in that：
In step 3, calculating has time effective moon samming where day samming data, is tested using the effectively monthly gentle accumulated temperature actual value
The first corresponding relation is demonstrate,proved, the second corresponding relation is verified using the effective month samming, accumulated temperature actual value, accumulated temperature number of days.
5. the method that accumulated temperature and accumulated temperature number of days are obtained based on moon samming according to claim 4, it is characterised in that：Step 3
In, the effective monthly gentle accumulated temperature actual value place time for verifying is different from all times described in step 1.
6. the method that accumulated temperature and accumulated temperature number of days are obtained based on moon samming according to claim 5, it is characterised in that：Step 3
In, the simulation for verifying the first corresponding relation and the second corresponding relation using mean absolute error, average deviation, root-mean-square error is imitated
Really.
7. the method that accumulated temperature and accumulated temperature number of days are obtained based on moon samming according to claim 6, it is characterised in that：Step 3
In, the simulation effect includes numerical values recited and Annual variations.
8. the method that accumulated temperature and accumulated temperature number of days are obtained based on moon samming according to claim 1, it is characterised in that：Step 3
In, all times where calculating day samming data using method average month by month are effective with last in first effective moon
Moon samming between month.
9. the method that accumulated temperature and accumulated temperature number of days are obtained based on moon samming according to claim 1, it is characterised in that：Step 1
In, the accumulated temperature in all times where calculating day samming data using moving average method on the five starts day, accumulated temperature closing day.
10. the method that accumulated temperature and accumulated temperature number of days are obtained based on moon samming according to claim 1, it is characterised in that：Step 1
In, the target area is the region observed all the year round in observation website.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611146491.6A CN106777963A (en) | 2016-12-13 | 2016-12-13 | A kind of method that accumulated temperature and accumulated temperature number of days are obtained based on moon samming |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611146491.6A CN106777963A (en) | 2016-12-13 | 2016-12-13 | A kind of method that accumulated temperature and accumulated temperature number of days are obtained based on moon samming |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN106777963A true CN106777963A (en) | 2017-05-31 |
Family
ID=58876524
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201611146491.6A Pending CN106777963A (en) | 2016-12-13 | 2016-12-13 | A kind of method that accumulated temperature and accumulated temperature number of days are obtained based on moon samming |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106777963A (en) |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060074560A1 (en) * | 2003-01-31 | 2006-04-06 | Dyer James S | Method and system of evaluating performance of a crop |
| CN103210864A (en) * | 2013-04-25 | 2013-07-24 | 山东省海洋水产研究所 | Octopus ocellatus embryonic development stage dividing method based on growth accumulated temperature |
-
2016
- 2016-12-13 CN CN201611146491.6A patent/CN106777963A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060074560A1 (en) * | 2003-01-31 | 2006-04-06 | Dyer James S | Method and system of evaluating performance of a crop |
| CN103210864A (en) * | 2013-04-25 | 2013-07-24 | 山东省海洋水产研究所 | Octopus ocellatus embryonic development stage dividing method based on growth accumulated temperature |
Non-Patent Citations (1)
| Title |
|---|
| YUNHE YIN: ""A new method for generating the thermal growing degree-days and season in china during the last century", 《INTERNATIONAL JOURNAL OF CLIMATOLOGY》 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Best et al. | The plumbing of land surface models: benchmarking model performance | |
| Novak et al. | Precipitation and temperature forecast performance at the Weather Prediction Center | |
| Soden et al. | An assessment of climate feedbacks in coupled ocean–atmosphere models | |
| Rutherford et al. | Climate field reconstruction under stationary and nonstationary forcing | |
| Praveen et al. | On the relationship between mean monsoon precipitation and low pressure systems in climate model simulations | |
| Wernli et al. | Spatial forecast verification methods intercomparison project: Application of the SAL technique | |
| Plavcan et al. | Automatic and probabilistic foehn diagnosis with a statistical mixture model | |
| Mitchell et al. | Comparison of predictions and observations to assess model performance: a method of empirical validation | |
| King et al. | On the linearity of local and regional temperature changes from 1.5 C to 2 C of global warming | |
| Estévez et al. | Quality assurance procedures for validating meteorological input variables of reference evapotranspiration in mendoza province (Argentina) | |
| Krakauer et al. | Precipitation trends over the Indus basin | |
| Zitouna-Chebbi et al. | Observing actual evapotranspiration from flux tower eddy covariance measurements within a hilly watershed: Case study of the Kamech site, Cap Bon Peninsula, Tunisia | |
| Guan et al. | Improvement of statistical postprocessing using GEFS reforecast information | |
| CN116450700B (en) | Polar orbit satellite earth surface temperature time normalization method and device and electronic equipment | |
| Steiger et al. | A pseudoproxy assessment of data assimilation for reconstructing the atmosphere–ocean dynamics of hydroclimate extremes | |
| Schepen et al. | On the joint calibration of multivariate seasonal climate forecasts from GCMs | |
| Wang et al. | Improving the simulation of tropical convective cloud-top heights in CAM5 with CloudSat observations | |
| You et al. | Quality control of weather data during extreme events | |
| Pitman et al. | Global and regional comparison of daily 2-m and 1000-hPa maximum and minimum temperatures in three global reanalyses | |
| Bailey et al. | Adaptive blending of model and observations for automated short-range forecasting: Examples from the Vancouver 2010 Olympic and Paralympic Winter Games | |
| Clark et al. | An automated, multiparameter dryline identification algorithm | |
| Seo et al. | Evaluation of Land–Atmosphere Coupling Processes and Climatological Bias in the UFS Global Coupled Model | |
| Tang et al. | Point downscaling of surface wind speed for forecast applications | |
| Hoover et al. | Forecast impact of assimilating aircraft WVSS-II water vapor mixing ratio observations in the Global Data Assimilation System (GDAS) | |
| Rassl et al. | Climatological drought monitoring in Switzerland using EUMETSAT SAF satellite data |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20170531 |
|
| RJ01 | Rejection of invention patent application after publication |