Construction of Climate Suitability Evaluation Model for Winter Wheat and Analysis of Its Spatiotemporal Characteristics in Beijing-Tianjin-Hebei Region, China

Abstract

Climate change alters climatic factors, which in turn affect the suitability of crops to grow. Winter wheat is a major crop in the Beijing-Tianjin-Heibei region of China. To assess the climate factors on winter wheat production, the meteorological data (temperature, precipitation, sunshine, etc.) from 25 stations in the target region the Beijing-Tianjin-Hebei region of China from 1961 to 2010, the winter wheat yield data from 1978 to 2010, and the growth stages were used. A model of the suitability of light, temperature, and water was subsequently developed to quantitatively analyze the spatial and temporal variability of the suitability of the winter wheat to the climate of the region. Temperature suitability was high during the sowing and grouting periods (temperature suitability peaks at 0.941 during grouting) and lowest in the rejuvenation period. In terms of spatial distribution, it is strong in the south and low in the north, and it exhibits a gradual increase in interannual variation. Precipitation suitability fluctuates steadily, with a peak in the tillering stage and a trough in the jointing stage. In terms of spatial distribution, it is highest in the northeast and decreases in the west; in inter-annual changes, it fluctuates strongly with weak overall growth. Sunshine suitability is stable at 0.9 or above. In spatial distribution, it is high in the northwest and low in the southeast, and it decreases slowly in the interannual variations. The trend of climatic suitability is consistent with temperature and precipitation, showing a pattern of falling first and then rising. In terms of spatial distribution, the overall climate suitability is high in the south and low in the north. In inter-annual changes, climate suitability generally increases slowly. Temperature and precipitation are key factors. Moisture stress became the most important factor for winter wheat cultivation in the region. Sunshine conditions are typically sufficient. This study provides a theoretical basis for a rational layout of winter wheat growing areas in the Beijing-Tianjin-Hebei region and the full utilization of climatic resources.

1. Introduction

Huge fluctuations in the statistical significance of the climate in the mean state or climate changes that last for a longer period of time are collectively referred to as climate change [1], global climate change is an important issue in today’s natural environmental change, climate change does not only exist in scientific research, it has deeply affected the process of human society. From static to dynamic and from stable to sudden change is the shift in people’s understanding of climate change in recent years [2,3]. Temperature, precipitation, and sunshine hours are the three major factors affecting agricultural production [4,5,6].

Changes in various climatic factors have impacts on the suitability of crop growth [7]. They can even affect the changes in civilizations on the larger scale of history [8]. Scientific guidance for crop production requires long-term research at the physiological level of winter wheat. At present, the evaluation of the suitability of climate resources for crop growth has gradually moved from qualitative to quantitative [9,10]. Climate suitability is a quantitative index that measures the degree of matching between climatic conditions and the growth needs of crops [11]. It is of great significance to carry out the construction of the suitability model for the climatic conditions in different regions.

Significant breakthroughs in the localization of climate suitability models and the simulation of climate change scenarios have been achieved globally. The UK used the CERES-Wheat dynamic model to simulate climate scenarios for the South East in 2050, and found that increased temperature alone reduced yields, and model optimization showed that early sowing in September with a sandy loam (Hamble silt loam) was the optimal management strategy to achieve increased yields, while late sowing in November reduced yields the most dramatically [12]. This study provides a management paradigm for climate-smart agriculture. The Indian Agricultural Research Institute used AHP and GIS technology to analyze the suitability of five cereals in Haryana, India, combined with a variety of environmental factors, and determined the proportion of suitable areas for each crop, and found that pearl millet and sorghum had the best adaptability, which provided a basis for decision-making on the distribution and sustainable development of agricultural production in the region [13]. African scholars effectively quantified the spatiotemporal evolution of climate suitability for wheat in the Upper Blue Nile River Basin of Ethiopia by integrating the Global Agro-Ecological Zones (GAEZ) model with CMIP6 climate scenario data. Their analysis revealed that under the high-emission scenario (SSP585), the area of highly suitable land is projected to decrease from 24.21% to 13.31% by the 2080s, indicating a significant decline driven by thermo-hydrological stress and exhibiting spatial heterogeneity [14].

Climate suitability studies of crops in China have been characterized by regionalization and refinement. In terms of model construction, Wang et al. combined maize phenology data to establish a single-factor and integrated climate suitability model for temperature, precipitation, light and integrated climate suitability for maize at different growth stages in the Northeast and Yellow Huaihai regions, which yielded the mean values of temperature, precipitation, light and integrated suitability of 0.77, 0.49, 0.87, and 0.65 for maize growth cycle in Northeast China, and 0.98, 0.53, 0.73, and 0.70 for the Yellow Huaihai region, 0.73 and 0.70 in the Yellow Huaihai region, and accordingly proposed an optimization strategy for maize cultivation in the two regions [15]. Tang et al. screened five optimal models based on the General Circulation Model (GCM) of CMIP5, combined with mathematical methods, and analyzed the climate suitability of winter wheat in the North China Plain in terms of moisture, temperature, and solar radiation in the present and the future (2021–2100). The spatial and temporal distributions found that in the future, the moisture suitability increased from 0.30 to 0.40, the temperature suitability decreased from 0.80 to 0.75, the solar radiation suitability showed an increasing trend, and the comprehensive suitability slightly improved [16]. In terms of technical methods, Zhao et al. coupled the cumulative biomass simulated by the APSIM model with multi-climatic indicators, such as the climate suitability index and extreme climate index, in a study of wheat yield prediction in the North China Plain, and constructed a prediction model by using machine learning algorithms such as Random Forest (RF), Lightweight Gradient Boosting Machine (LGB), and Multivariate Linear Regression (MLR), and the results showed that the RF model had the best performance, the flowering to filling period was the best prediction time, the prediction accuracy of irrigated area was higher than that of rainfed area, and APSIM simulated biomass and climate suitability index played an important role in the model [17].

The Beijing-Tianjin-Hebei region of China has a warm temperate monsoon climate, which is suitable for winter wheat growing year-round, making it a traditional winter wheat growing region. Current studies on the climate suitability of winter wheat in the Beijing-Tianjin-Hebei region are mostly concentrated in the Huang-Huai-Hai region or parts of North China Plain [18,19,20,21]. Although they have provided certain basis for agricultural production layout in specific areas, there are two obvious limitations: first, the research scope fails to fully cover the entire Beijing-Tianjin-Hebei region, making it difficult to systematically reflect the comprehensive impact of complex climatic differences within the region on winter wheat growth. In particular, the climatic adaptability characteristics of marginal areas such as northern and eastern Hebei have long lacked systematic exploration, resulting in a lack of unified scientific support for planting planning at the whole-region scale [22,23,24]. Second, in terms of time dimension, existing studies are mostly based on short time series, which insufficiently reveal the synergistic evolution law of light, temperature, water, and other climatic factors and their cumulative impact on winter wheat suitability at long-term interdecadal scales, making it difficult to cope with long-term risks faced by agricultural production under the background of climate change [25,26].

In response to these deficiencies, this study expands the research scope to the entire Beijing-Tianjin-Hebei region and establishes a 50-year light–temperature–water suitability model. Through large-scale spatial calculations and analyses, it examines the climate suitability and its variability patterns across the entire region. Grid-based calculations show that the correlation coefficient between areas with a climatic suitability index above 0.7 and the actual winter wheat growing areas is 0.516, which effectively reflects the true distribution of winter wheat cultivation. The purpose of this study is to fill the research gap on climate suitability in the marginal areas of the Beijing-Tianjin-Hebei region, clarify the differential impacts of climatic factors on winter wheat growth across different sub-regions, and improve the theoretical system for regional winter wheat climate adaptation. Through long-term interdecadal analysis, it captures the potential trends in climate change impacts across the entire winter wheat growing season, thereby providing a scientific basis for optimizing planting layouts, efficiently utilizing climate resources, and formulating climate change adaptation strategies in this region.

2. Materials and Methods

2.1. Source of Data

The data in this study is based on 25 stations and meteorological data in the Beijing-Tianjin-Hebei region (see Figure 1 for the distribution of stations). Meteorological data includes temperature, precipitation, hours of sunshine, relative humidity, maximum and minimum air temperature, and station information includes longitude, latitude, and elevation data (

Table 1. Station information.

Station	Region	Longitude	Latitude	Altitude (m)
Zhangbei	Heibei	114.7	41.15	1393.3
Yuxian	Heibei	114.57	39.83	909.5
Shijiazhuang	Heibei	114.42	38.03	81
Xingtai	Heibei	116.5	37.07	183
Fengning	Heibei	116.63	41.22	735.1
Weichang	Heibei	117.75	41.93	892.7
Zhangjiakou	Heibei	114.88	40.78	772.8
Huailai	Heibei	115.5	40.4	570.9
Miyun	Beijing	116.87	40.38	71.8
Chengde	Heibei	117.95	40.98	422.3
Zunhua	Heibei	117.95	40.2	54.9
Qinglong	Heibei	118.95	40.4	254.3
Qinhuangdao	Heibei	119.52	39.85	2.4
Beijing	Beijing	116.47	39.8	32.3
Langfang	Heibei	116.38	39.12	8.9
Tianjin	Tianjin	117.07	39.08	3.5
Tangshan	Heibei	118.15	39.67	23.2
Laoting	Heibei	118.88	39.43	8.5
Baoding	Heibei	115.52	38.85	16.8
Raoyang	Heibei	115.73	38.23	19
Cangzhou	Heibei	116.83	38.33	10.8
Botou	Heibei	116.55	38.08	13.2
Tanggu	Tianjin	117.72	39.05	4.8
Huanghua	Heibei	117.35	38.37	4.5
Nangong	Heibei	115.38	37.37	27.4

), with a time scale from 1961 to 2010. The above data is from the China Meteorological Data Service Centre. Winter wheat yield data was obtained from Hebei Province, Beijing Municipal Bureau of Statistics and Tianjin Municipal Bureau of Statistics, covering the period 1978–2010.

2.2. Growth Stage Division

Based on the station meteorological data and the growth characteristics of winter wheat in Beijing-Tianjin-Hebei, and combined with the results of previous studies [27,28,29], winter wheat was divided into seven growth stage, which were sowing period (early to late October), tillering stage (late October to early to mid-December), overwintering period (mid to late December to early February), rejuvenation period (mid-February to early March), jointing stage (mid-March to early April), tasseling stage (mid-April to early May), grouting period (mid-May to late June). Winter wheat is an inter-annual crop, so the sowing period and tillering period should be counted according to the current year, and the overwintering period should be treated as inter-annual, and constitute a growing season with the other four growth stages of the following year [30].

2.3. Temperature Suitability Modeling

Combining the results of previous research [31,32], the temperature suitability model of winter wheat is constructed as follows.

$$\mathrm{F}\left(\mathrm{t}\right)={\displaystyle \frac{{(t-t_1)(t_2-t)}^B}{{(t_0-t_1)(t_2-t_0)}^B}},$$

(1)

$$\mathrm{B}={\displaystyle \frac{t_2-t_0}{t_0-t_1}},$$

(2)

where F(t) represents the temperature suitability of a certain growth stage, t is the average daily temperature, t₁ is the lower limit temperature, t₂ is the upper limit temperature, and t₀ is the optimal temperature.

According to the Beijing-Tianjin-Hebei winter wheat growth data for localization, the process of adjusting the parameters involves combining the existing parameters in the relevant literature, but due to the inconsistency of the method of the division of the growth stage and the study area it cannot be directly quoted from the conclusions of the predecessors. So, here we correct the existing parameters, calculated to obtain the corresponding results, and then determine the parameters according to the actual situation of Beijing-Tianjin-Hebei, and finally obtain the parameters of the various types of thresholds listed in

Table 2. Temperature suitability model parameters.

Reproductive Period	t1	t2	t0	B
Sowing period	3	25	17	0.57
Tillering stage	0	20	13	0.54
Overwintering period	−10	8	1	0.64
Rejuvenation period	1	16	5	2.75
Jointing stage	8	18	12	1.5
Tasseling stage	9	25	18	0.78
Grouting period	10	30	23	0.54

F(t) = 0 when t < t₁ or t > t₂, F(t) = 0 when t = t₀.

.

2.4. Precipitation Suitability Modeling

Precipitation is the main source of soil moisture and crop moisture, and its impact on crop growth suitability has hierarchical characteristics, most of the current international common precipitation suitability model is based on the crop evapotranspiration model, crops in different precipitation stages will show different physiological responses, drought indicators can be used to classify the different stages of crop precipitation demand [33]. In this study, we refer to the evapotranspiration calculation method and combine it with the actual precipitation situation in the Beijing-Tianjin-Hebei region to construct a model of precipitation suitability.

$$F(r)=\left\{\begin{array}{cc}r0/r_1& r<r_1\\ 1& r_1\le r\le r_2\\ r0/r_2& r>r_2\end{array},\right.$$

(3)

where F(r) is the precipitation suitability, r is the precipitation in a certain decade, r₁ is the light drought precipitation, and r₂ is the light flooding precipitation. r₁ and r₂ can be determined by the drought index, based on the drought and flooding index of winter wheat in Hebei [34,35], the ratio of the actual precipitation to the water demand of the crop, r₀ is less than 60% for light drought, and more than 150% for light flooding, and the ratio of actual precipitation and crop water demand r₀ is less than 60% for light drought and more than 150% for light flooding, and the ratio of actual precipitation to crop water demand r₀ when in the range between 60% and 150% is the suitable level. Therefore, r₁ is taken as 0.6r₀ and r₂ is taken as 1.5r₀. Based on the values of the meteorological parameters, the reference crop evapotranspiration ET₀ was multiplied by the crop coefficients Kc for each growth stage of winter wheat to obtain the crop water requirement of winter wheat [36].

$${\mathrm{r}}_0={\mathrm{K}}_{\mathrm{c}}\times {\mathrm{E}\mathrm{T}}_0$$

(4)

The values of crop coefficient Kc parameters [37,38,39] are shown in

Table 3. Parameters of crop coefficient.

Crop Coefficient	Reproductive Period
	Sowing Period	Tillering Stage	Overwintering Period	Rejuvenation Period	Jointing Stage	Tasseling Stage	Grouting Period
Kc	0.67	0.74	0.64	0.76	0.9	1.22	0.98

.

ET₀ can be calculated by evapotranspiration model, and the known evapotranspiration models based on conventional meteorological data are Penman–Monteith modified by the Food and Agriculture Organization of the United Nations, Priestley–Taylor, Hargreaves–Samani, Bowen Ratio, and Eddy Covariance [40]. Due to the large study area, the Priestley–Taylor method is applicable to the evapotranspiration model for large-scale wet surfaces [41], so this evapotranspiration model is adopted in this study as the calculation method of ET₀, with the following equations:

$$\mathrm{E}{\mathrm{T}}_0=\mathsf{\alpha }{\displaystyle \frac{∆}{∆+\mathsf{\gamma }}}{\displaystyle \frac{{\mathrm{R}}_{\mathrm{n}}}{\mathsf{\lambda }}},$$

(5)

where α is a constant (α = 1.26), Δ is the slope of the saturated water vapor pressure–temperature curve, γ is the dry temperature sphere constant, and R_n is the net radiation from the canopy surface, which is calculated as follows.

$$∆={\displaystyle \frac{2504\mathrm{e}\mathrm{x}\mathrm{p}\left(\frac{17.27\mathrm{t}}{\mathrm{t} + 237.3}\right)}{{(\mathrm{t}+237.3)}^2}}$$

(6)

$$\mathsf{\gamma }=0.00163{\displaystyle \frac{\mathrm{P}}{\mathsf{\lambda }}}$$

(7)

$${\mathrm{R}}_{\mathrm{n}}={\mathrm{R}}_{\mathrm{n}\mathrm{s}}-{\mathrm{R}}_{\mathrm{n}\mathrm{l}}$$

(8)

In the formulas, t is the air temperature of a certain decade, P is the barometric pressure, $\mathsf{\lambda }$ = 2.45, R_ns is the net shortwave radiation, and R_nl is the net longwave radiation.

They are calculated by the formulas, respectively:

$$\mathrm{P}=101.3{\left({\displaystyle \frac{293-0.0065H}{293}}\right)}^{5.62,}$$

(9)

$${\mathrm{R}}_{\mathrm{n}\mathrm{s}}=0.77\left(0.25+0.5{\displaystyle \frac{\mathrm{n}}{\mathrm{N}}}\right){\mathrm{R}}_{\mathrm{a}},$$

(10)

$${\mathrm{R}}_{\mathrm{a}}=37.6{\mathrm{d}}_{\mathrm{r}}\left({\mathsf{\omega }}_{\mathrm{s}}\mathrm{s}\mathrm{i}\mathrm{n}\mathsf{\phi }\mathrm{s}\mathrm{i}\mathrm{n}\mathsf{\delta }+\mathrm{c}\mathrm{o}\mathrm{n}\mathsf{\phi }\mathrm{c}\mathrm{o}\mathrm{s}\mathsf{\delta }\mathrm{s}\mathrm{i}\mathrm{n}{\mathsf{\omega }}_{\mathrm{s}}\right),$$

(11)

$${\mathrm{d}}_{\mathrm{r}}=1+0.033\cos \left(0.0172\mathrm{J}\right),$$

(12)

$$\mathsf{\delta }=0.409\sin \left(0.0172\mathrm{J}-1.39\right),$$

(13)

$${\omega }_s=\arccos \left(-\mathrm{t}\mathrm{a}\mathrm{n}\mathsf{\phi }\mathrm{t}\mathrm{a}\mathrm{n}\mathsf{\delta }\right),$$

(14)

$${\mathrm{R}}_{\mathrm{n}\mathrm{l}}=2.45\times {10}^9\left(1.35{\displaystyle \frac{0.25+0.5\frac{\mathrm{n}}{\mathrm{N}}}{0.75+2\ast {10}^{-5}\mathrm{H}}}-0.35\right)\left(0.34-0.14\sqrt{{\mathrm{e}}_{\mathrm{d}}}\right)\left({{\mathrm{T}}_{\mathrm{k}\mathrm{x}}}^4+{{\mathrm{T}}_{\mathrm{k}\mathrm{n}}}^4\right).$$

(15)

H is the altitude, ${\displaystyle \frac{n}{N}}$ is the percent insolation, R_a is the upper atmospheric radiation, d_r is the relative distance between the sun and the earth, ${\omega }_s{\omega }_s$ is the angle of sunset, $\mathsf{\phi }\mathsf{\phi }$ is the latitude, $\mathsf{\delta }\mathsf{\delta }$ is the solar declination, J is the number of days in the year, e_d is the actual water vapor pressure (obtained by multiplying the relative humidity of the air with the saturated water vapor pressure, which is obtained by the slope of the saturated water vapor pressure–temperature curve), T_kx is the maximum absolute air temperature, and T_(kn) is the minimum absolute air temperature.

2.5. Sunshine Suitability Modeling

The effect of light on the suitability of winter wheat can be understood as a fuzzy process, and similar to precipitation, it also switches between two states of suitability and unsuitability [42]. In this study, we set the number of sunshine hours reaching 70% as the threshold value of suitable sunshine hours s₀, i.e., when the sunshine ratio (actual sunshine hours/available sunshine hours) is above 70%, the light demand of winter wheat reaches the suitable state. The number of sunshine hours s ≥ s₀ is the highest economic yield of winter wheat that can be achieved under the clear sky state, that is, the appropriateness is 1, and the sunshine appropriateness affiliation function is constructed on the basis of this.

$$F(s)=\left\{\begin{array}{cc}{e}^{-{\left({\displaystyle \frac{s-s_0}{b}}\right)}^2}& s<s_0\\ 1& s\ge s_0\end{array},\right.$$

(16)

where F(s) is the sunshine suitability, s is the number of hours of sunshine in a certain period of time, s₀ is the sunshine percentage of 70% of the sunshine threshold, b is a constant, according to the Beijing-Tianjin-Hebei region of winter wheat growth characteristics of the localization process, after a number of parameter adjustments, the b values for each growth stage that best match the growth conditions of winter wheat in the Beijing-Tianjin-Hebei region were determined; s₀ (the threshold of suitable sunshine hours, corresponding to 70% of the available sunshine hours) was obtained by calculating the sunshine ratio. The specific values of s₀ and b for each growth stage are detailed in

Table 4. Parameters of sunshine suitability model.

Parameters of Sunlight Suitability	Reproductive Period
	Sowing Period	Tillering Stage	Overwintering Period	Rejuvenation Period	Jointing Stage	Tasseling Stage	Grouting Period
s0	8.57	7.40	7.17	8.32	9.11	9.96	10.60
b	4.15	4.00	4.16	4.23	4.50	4.61	4.96

.

2.6. Determination of Weights

The temperature, precipitation, and sunshine suitability of each growth stage were first correlated with meteorological yield (obtained via trend separation), and the correlation coefficients were standardized to obtain the weights for each growth stage [43]. As shown in

Table 5. Weights for each growth stage.

Weight	Reproductive Period
	Sowing Period	Tillering Stage	Overwintering Period	Rejuvenation Period	Jointing Stage	Tasseling Stage	Grouting Period
Temperature suitability	0.11	0.21	0.19	0.16	0.06	0.14	0.13
Precipitation suitability	0.12	0.10	0.11	0.12	0.14	0.20	0.21
Sunshine suitability	0.08	0.05	0.08	0.18	0.15	0.21	0.25

, the weights vary by growth stage and factor: for example, temperature suitability has the highest weight in the tillering stage (0.21), while precipitation suitability is most influential in the grouting stage (0.21), reflecting the differential demand for climatic factors during winter wheat development.

Using the cumulative model, the suitability of each meteorological factor (temperature, precipitation, sunshine) was calculated by summing their stage-specific weighted components. Similarly, the correlation coefficients between each factor’s suitability and meteorological yield were standardized to obtain their total weights in the integrated climate suitability model [44].

Table 6. Climate suitability model weights.

Meteorological Factors	Temperature	Precipitation	Sunshine
Weights	0.25	0.28	0.47

shows that sunshine has the highest total weight (0.47), followed by precipitation (0.28) and temperature (0.25), indicating that sunshine is the most stable contributor to climate suitability in the study area.

2.7. Climate Suitability Model Construction

The climatic suitability model is constructed using the cumulative method, where the suitability components of the meteorological elements are derived from the weights of each meteorological element, which are cumulated.

$$\mathrm{F}\left(\mathrm{c}\right)=\mathrm{m}\times \mathrm{F}\left(\mathrm{t}\right)+\mathrm{n}\times \mathrm{F}\left(\mathrm{r}\right)+\mathrm{q}\times \mathrm{F}\left(\mathrm{s}\right),$$

(17)

where F(c) is the climate suitability, m, n, q are the corresponding weights.

2.8. Accumulated Temperature Suitability

Accumulated temperature suitability is a heat resource suitability calculation method based on the temperature suitability model, and this study adopts a similar formula.

$$\mathrm{F}\left(\mathrm{a}\right)={\displaystyle \frac{{(a-a_1)(a_2-a)}^p}{{(a_0-a_1)(a_2-a_0)}^p}}$$

(18)

$$\mathrm{p}={\displaystyle \frac{a_2-a_0}{a_0-a_1}}$$

(19)

F(a) is the accumulated temperature suitability, a is the accumulated temperature during the reproductive period, and a₁, a₂, and a₀ represent the lower limit, upper limit, and optimal accumulated temperature, respectively. Combined with the growth demand of winter wheat in the Beijing-Tianjin-Hebei region, the key parameters for accumulated temperature suitability were sorted out, including the lower limit (a₁), upper limit (a₂), optimal value (a₀) of accumulated temperature, and the parameter P (calculated via Formula (19)) for three critical periods: pre-wintering, overwintering, and full life span. The specific parameter values are listed in

Table 7. Parameters of accumulated temperature suitability model.

Reproductive Period	a1	a2	a0	P
pre-wintering	345	790	530	1.40
overwintering period	−430	−60	−210	0.68
full life span	1500	2600	2000	1.2

. For example, the optimal accumulated temperature (a₀) for the full life span is 2000, which provides a quantitative basis for evaluating heat resource adequacy.

3. Results

3.1. Characteristics of Suitability Change in Winter Wheat in Each Growth Stage

The data was processed and statistically calculated using the methods described above, and the climatic suitability of the Beijing-Tianjin-Hebei region was finally obtained. As can be seen from Figure 2, the temperature suitability reached 0.869 and 0.941 in the sowing and grouting periods, respectively, with high values, indicating that the temperature conditions in these two growth stages are very favorable to the growth of winter wheat, while the temperature suitability in the greening period was the worst, only 0.265, with fluctuating decreases from the sowing period to the greening period, and then a sharp rebound afterward. Precipitation suitability varied steadily, peaking at 0.743 during the tillering stage, declining to a trough value of 0.293 during the subsequent jointing stage, and eventually recovering to a level of 0.532 during the grouting stage. The sunshine suitability was stable above 0.9. The trend of climate suitability is consistent with the temperature and precipitation, showing the change rule of decreasing and then increasing, the same as the temperature, the sowing period and the grouting period are two high values, respectively, 0.832 and 0.829, the valley value and the precipitation suitability appeared in the jointing period, 0.614, and the sunshine suitability has always been maintained at a higher level, so it can be seen that the temperature and precipitation are the key factors influencing the climate suitability for winter wheat in the Beijing-Tianjin-Hebei region, that is, the Beijing-Tianjin-Hebei region is the most important area for the climate suitability. It can be seen that temperature and precipitation are the key factors affecting the climatic suitability of winter wheat in the Beijing-Tianjin-Hebei region. Specifically, the region has abundant sunshine, and such conditions do not generally become a limiting factor for winter wheat planting.

The degree of dispersion of the suitability components is analyzed by calculating the coefficient of variation for each growth stage, with specific values shown in

Table 8. List of coefficients of variation.

Reproductive Period	Sowing Period	Tillering Stage	Overwintering Period	Rejuvenation Period	Jointing Stage	Tasseling Stage	Grouting Period
Temperature suitability	5.01	19.85	18.52	82.96	66.77	9.04	1.83
Precipitation suitability	41.41	30.34	63.52	75.09	63.25	64.91	32.97
Sunshine suitability	4.54	1.03	1.19	4.15	3.29	4.29	4.31

. From the results: (1) Temperature suitability had the highest variation coefficient in the rejuvenation stage (82.96), matching its lowest suitability value (0.265) and confirming unstable temperature conditions during this period. (2) Precipitation suitability showed the highest variation in the rejuvenation stage (75.09) as well, even though its suitability (0.37) was not the lowest, indicating unreliable precipitation supply for winter wheat regrowth. (3) Sunshine suitability maintained low variation coefficients (≤4.54) across all stages, consistent with its stably high suitability (≥0.9), reflecting stable light conditions.

The degree of variation in temperature suitability was larger in the greening and jointing stages, while the suitability was at a low value, indicating that the temperature conditions in this growth stage were unstable and unfavorable to the growth of winter wheat [45]. The coefficient of variation in precipitation suitability gradually increased and reached a peak value of 75.09 at the greening stage, and the suitability of precipitation at this growth stage was not at the lowest value, but was also at the low value of 0.37, which showed that the precipitation at the greening stage could not meet the demand of winter wheat and was unstable, and it was also an important time to restrict the growth and development of winter wheat. The coefficient of variation in sunshine suitability appeared a more obvious trough in the tillering period, and at the same time, the sunshine suitability in the tillering period was at the maximum value of 0.987 in the whole life cycle, after analysis, the sunshine suitability in the 50-year period with the rate of 0.0002 per year slowly declined, and there was only a slight change, the tillering period of sufficient sunshine to help the pre-winter seedling, so that the stability of the sunshine conditions of the winter wheat carbon uptake will play a positive role. This stable sunshine condition will play a positive role in carbon absorption of winter wheat [46].

3.2. Characteristics of Inter-Annual Changes in Suitability over the Whole Life Span

Overall (see Figure 3), there was no obvious trend of change in the suitability indicators over the 50 years, but there were large differences in the degree of fluctuation of different suitability components. Temperature suitability, as shown in the line graph, was in a stable stage before the 1990s, and slightly increased after the 1990s, reaching a peak of 0.715 in 2008, and then rapidly declined back to 0.556 in the last two years, and analyzed, the temperature suitability generally increased at a rate of 0.032/10a, with a coefficient of variation of 10.4. The average value of temperature suitability above 0.5 makes the temperature conditions in the Beijing-Tianjin-Hebei region basically suitable for winter wheat cultivation, and there will be a tendency to improve year by year in the future. From the figure, it can also be seen that the fluctuation of precipitation suitability is the largest, and its coefficient of variation reaches 22.8, which is the highest among the four suitability models. Its average value is only 0.453, and the trend of change is 0.008/10a after regression analysis. This weak growth will not bring much positive effect under the large degree of dispersion, so the suitability of precipitation in Beijing-Tianjin-Hebei region cannot satisfy the growth requirements of winter wheat, and moisture stress becomes a limiting condition for winter wheat production in the region. The sunshine suitability has been stable at a high level for 50 years, except for the lowest value of 0.87 in 2003, the rest of the years are above 0.9, the degree of fluctuation is also very low, the coefficient of variation is only 2.24, and the overall change is a slow decline at a rate of 0.007/10a, which indicates that Beijing-Tianjin-Hebei has good sunshine conditions, and it can almost fully satisfy the winter wheat’s light demand for the past 50 years, though there is a declining trend. While there is a decreasing trend, the rate is low and the change is moderate, which will not have a huge impact on winter wheat production in the region. Climate suitability is roughly at the average level of temperature, precipitation and sunshine suitability, with an overall average value of 0.73, fluctuating up and down on the 0.7 scale. The analysis shows that the climate suitability grows slowly at the rate of 0.007/10a, with a coefficient of variation of 4.2, which shows that the overall level of climate suitability is high, with little fluctuation and change, and that the stable and comprehensive climate suitability is a necessary condition for the cultivation of winter wheat in a large area of the Beijing-Tianjin-Hebei region. A stable and comprehensive climate suitability is necessary for the large-scale cultivation of winter wheat in the Beijing-Tianjin-Hebei region.

The 50-year change in suitability in the Beijing-Tianjin-Hebei region generally reflects better temperature and sunshine conditions, poorer suitability of precipitation accompanied by strong fluctuations, and water scarcity as the main limiting condition. From the calculation of precipitation suitability, it can be understood that it is generated under the joint action of a complex set of meteorological factors. The frequent fluctuations in air humidity, wind speed, and solar radiation may be key in affecting precipitation. The stable and high situation indicates that the changes in meteorological factors in the Beijing-Tianjin-Hebei region are generally at a stable level, which is favorable for winter wheat growth.

3.3. Spatial Distribution of Climate Suitability

The spatial distribution of winter wheat suitability in the Beijing-Tianjin-Hebei region is shown in Figure 4.

The temperature suitability was significantly higher in the south and lower in the north in a stepwise distribution. The station with the lowest latitude, Xingtai in Ji’nan, correspondingly has the highest temperature suitability of 0.865, while the lowest value is at Zhangbei, 0.122, and most of the northern regions are below 0.5. Weak and semi-wintering winter wheat is poorly cold-resistant, and the temperature is the main limiting condition for this winter wheat in the northern region, which is susceptible to the effect of frost damage. The 0.6 mean contour passes through the central stations of Laoting, Zunhua, and Miyun. There is a clear northward bulge in the central section of the 0.72 contour, which is close to downtown Beijing and has a high compared to other areas at the same latitude due to the heat island effect brought about by the high degree of urbanization. The contour lines are roughly northwest–southeast oriented in the eastern region and southwest–northeast oriented in the western region, which is similar to the northern boundary of winter wheat analyzed by Wang Lianxi et al. based on the heat resources [47], indicating that the planting area of winter wheat based on the temperature conditions is mainly concentrated in the southeastern part of Beijing-Tianjin-Hebei region.

Precipitation suitability is highest in the northeastern part of the region, which is close to the coastline and on the windward side of the Yanshan Mountains, where the stations of Qinglong, Zunhua, and Chengde are located, with Qinglong being the highest station at 0.527. The barrier of the mountains gradually reduces the precipitation, and the large plains restrict the formation of fronts, so that it can be seen that the precipitation suitability decreases towards the west, and there are two north–south oriented stations at the meridian positions of 117° E, 117.5° E, and 117.5° E. At the E meridian position, there are two north–south equidistant dividing lines and two low-value troughs in the Huailai and Raoyang-Baoding areas, with the precipitation suitability values of 0.389, 0.407, and 0.399, respectively.

The overall level of insolation suitability is high, mostly above 0.9, and in order to observe more closely at its distribution characteristics, the contour spacing of this map was refined to 0.02, divided into five equal parts for temperature and precipitation. The direction of sunshine suitability is not as obvious as that of temperature and precipitation, and the overall distribution is high in the northwest and low in the southeast, but in some areas, there are peaks or troughs that do not match the surrounding suitability trend, such as Huailai, which is as high as 0.946, and Tianjin, where it is as low as 0.88, and the overall sunshine conditions in the Beijing-Tianjin-Hebei region are able to satisfy the growth needs of winter wheat.

The distribution of climate suitability in Beijing-Tianjin-Hebei region is roughly characterized by high in the south and low in the north, with a stepwise distribution from the low value to the high value. The highest value is 0.779 in Cangzhou, and the lowest value is 0.619 in Zhangbei, the suitability is more than 0.5, but none of them are more than 0.8. The overall climate suitability is better, and the contour line of Wailai is shifted, and the sufficient light resources play a certain role in increasing the suitability of the climate of the region. In the southern part of Beijing, the contour offset phenomenon is similar to the distribution of temperature suitability, and the data verified that this offset is more affected by the temperature conditions.

3.4. Spatial Distribution of Accumulated Temperature Suitability

As shown in Figure 5, the distribution of accumulated temperature suitability is in the shape of an inverted L, decreasing gradually from south to north in Jibei area, and from east to west in Ji’nan, Beijing, and Tianjin areas, with the highest station in Laoting, reaching 0.865, and the lowest station in Zhangbei, approaching 0.

3.5. Characteristics of Spatial Change in Climate Suitability

In order to visualize the trend of climatic suitability, considering the small base of suitability, the propensity rate for each meteorological factor and climate suitability are calculated by inter-decade in this study, with the results presented in Figure 6.

The distribution of the propensity rate of temperature suitability is high in the area from Cangzhou to the south of Beijing, and the highest value is in Langfang area, with a value of 0.057/10a, which indicates that the temperature conditions of winter wheat growing season in this area are improving at a faster rate. The tendency rate of temperature suitability in northern Hebei gradually decreases with the increasing latitude, and the region with the low value is in the area of Weichang and Chengde, where the tendency rate is 0.009/10a and 0.001/10a, respectively. The tendency rate decreases from east to west, with an average value of around 0.027/10a for the area from Shijiazhuang to Yuxian. Overall, the temperature suitability propensity rates are all above 0, which means that the temperature conditions in the Beijing-Tianjin-Hebei region are increasingly able to meet the heat demand of winter wheat, while the southeastern region has a clear growth advantage over the rest.

The precipitation suitability propensity rate gradually increases from southwest to northeast, with the lowest value of −0.009/10a in Xingtai and the highest value of 0.028/10a in Weichang, which are the southernmost and northernmost stations in the Beijing-Tianjin-Hebei region, respectively. The propensity rates in Beijing and Baoding are high compared to the values in other regions at the same latitude, 0.017/10a and 0.008/10a, respectively. The region between the two locations shows a ridge-like distribution that protrudes to the south. In the southeast, there is a small region of high values, in which stations Botou and Huanghua have propensity rates of 0.011/10a and 0.012/10a, respectively. The overall value of the propensity rate of precipitation suitability in Beijing-Tianjin-Hebei is on the low side, with the highest value about half of that of the temperature suitability, and the precipitation suitability of north and south is opposite, and the increasing trend in the north is more significant than that of the decreasing trend in the south.

Since the sunshine suitability is fundamentally above the high level of 0.9, the range of variation is extremely narrow, so that the absolute value of the propensity rate exceeds 0.01 only at five stations. The regularity of propensity rate distribution is also less evident, with large differences in values between neighboring sites and no smooth spatial variation process. Yuxian, Fengning, Raoyang, Xingtai, and Tangshan are all located in the center of the high-value area, with values of 0.0006/10a, −0.0013/10a, −0.0007/10a, −0.0013/10a, and 0.0006/10a, respectively. In the east–central region, the propensity rate gradually decreases to form a trough of low-values, with Chengde, Zunhua, and Miyun being the control centers of the low-value area, with the specific values of −0.0151/10a, −0.0152/10a, and −0.0158/10a, respectively. Generally, the negative area of the propensity rate of insolation suitability occupies most of the area, and the center of the high-value area still exists with three negative stations, so it can be seen that decreasing year by year is the main trend of the insolation suitability of the Beijing-Tianjin-Hebei region.

Except for Chengde, the rest of the stations have positive values, and the distribution gradually decreases from the center to the surroundings, and the central high value area exists in Beijing and its south, which coincides with the high value area of temperature suitability, indicating that the growth of temperature suitability is the key to the increase in climate suitability in this region, in which Beijing reaches 0.014/10a, and Langfang in the south is 0.012/10a. Under the influence of the Chengde station, a negative/low-value area of sunshine suitability has formed in the northeastern part of the region, which represents the main distribution trend of sunshine suitability across the Beijing-Tianjin-Hebei region. This low-value area has a central tendency rate of −0.002/10a, and the decrease in sunshine suitability is the primary driver behind the formation of this low-value zone. According to the distribution characteristics of the propensity rate of climate suitability, it can be judged that, in the five inter-decade period, the overall climate suitability is on the rise, and the climate environment for the growth of winter wheat improves year by year, among which, the central region is the most significant, the growth rate of the east and west sides slows down gradually, and the suitability along the area of Chengde has a slight decline.

3.6. Characteristics of Changes in Accumulated Temperature Suitability

As shown in Figure 7, in the Beijing-Tianjin-Hebei region, there is a high value of accumulated temperature suitability tendency rate in the northwestern region and a low value in the southeastern region. This is inversely proportional to the distribution of temperature suitability tendency rate, with the highest point in Zhangjiakou at 0.097 and the lowest point in Xingtai at −0.11. The variation in the accumulated temperature suitability is significantly higher than the others, and the absolute value of the stations is generally more than 0.05 within the region.

3.7. Comparative Analysis of Temperature Suitability and Accumulated Temperature Suitability

In order to better reflect the impact of changes in heat resources on the winter wheat suitability in the Beijing-Tianjin-Hebei region under the background of global warming, the accumulated temperature suitability is further calculated based on the temperature availability model. From the calculation results of the suitability expressed by the two types of heat resources, the accumulated temperature suitability is close to the temperature suitability in the numerical range, with the lowest value close to 0 and the highest value not exceeding 0.87. But there is a big difference between the distribution and the temperature suitability, with the high temperature suitability area concentrated in the south, while the accumulated temperature suitability is concentrated in the east. The reason for the difference is mainly due to the fact that negative temperatures accumulated in the southwestern part of Hebei during the overwintering period often. This difference is mainly due to the fact that the negative accumulated temperature in the overwintering period in the southwest of Hebei province often exceeded the minimum threshold, and winter wheat could not obtain sufficient heat security in the overwintering period. In the distribution of the propensity rate, there is also an inversion between the two, positive and negative, the temperature suitability propensity rate is positive in the whole domain, while the positive and negative of the accumulated temperature suitability high-value and low-value areas are diametrically opposite, and the accumulated temperature conditions in the northwest and southeast regions are reversed. Therefore, the difference between these two types of suitability should also be noted in specific applications.

4. Discussions

4.1. Changes in Suitability During Each Growth Stages

Temperature suitability in the sowing and grouting period can fully meet the growth needs of winter wheat, but from the overwintering period to the greening period, the temperature changes are not conducive to the growth and development of winter wheat, overwintering heat instability will affect the rate of greening of winter wheat in the second spring, too low will cause frost damage, too high will prolong tillering, affecting the storage of organic matter. The high inter-annual variability (CV = 82.96) statistically confirms that the low temperature suitability observed during the rejuvenation stage is not an anomaly but a consistent challenge, highlighting the critical need for protective measures against late frosts or temperature fluctuations. Moisture deficit has always been an important factor limiting winter wheat cultivation in the Beijing-Tianjin-Hebei region, and precipitation suitability is numerically low, with the overall level below 0.5, while the excessively high coefficient of variation also reflects the large fluctuation in precipitation suitability changes. The jointing stage is the stage with the worst precipitation suitability, with suitability only at 0.293, and in the future cultivation of winter wheat, emphasis should be placed on the maintenance of water in this growth stage or on supplemental Irrigation. The overall sunshine suitability was stable above 0.9, and the Beijing-Tianjin-Hebei region had less precipitation and less clouds, so most of the solar radiation could reach the ground, which provided good and stable light conditions for the whole reproductive period of winter wheat [48,49]. The trend of integrated climate suitability during the reproductive period of winter wheat reflects that temperature and precipitation are the dominant factors determining the change in climate suitability of winter wheat in the Beijing-Tianjin-Hebei region. The surplus or deficit of temperature and precipitation in a particular reproductive stage guides the change in climate suitability, while sufficient sunshine ensures that the climate suitability will not be too low. It is stable at 0.5 or above during the whole reproductive period.

The “first decreasing then increasing” trend of climate suitability is essentially a result of the phenological matching between winter wheat growth and seasonal climate rhythm. From sowing to overwintering, the gradual decrease in ambient temperature leads to a drop in temperature suitability (from 0.869 to above 0.5), which drives the initial decline of comprehensive suitability; from overwintering to grouting, temperature rebounds to the optimal range for growth, and precipitation suitability recovers significantly (from 0.293 in jointing stage to 0.532 in grouting stage). Meanwhile, the stably high sunshine suitability (≥0.9) provides a “baseline support” for photosynthesis, jointly promoting the rebound of comprehensive climate suitability. This dynamic matching relationship reveals the phased regulation of climate factors on winter wheat growth.

In summary, the climatic conditions in the Beijing-Tianjin-Hebei region can basically meet the growth needs of winter wheat, but in the greening and jointing period, we should pay attention to the possible adverse effects of changes in temperature and precipitation and make preparations for protection in advance.

4.2. Spatial–Temporal Distribution and Variation Trend of Suitability

Spatial distribution of each single meteorological factor suitability of the existence of large differences between the temperature suitability from south to north gradually decreased, precipitation suitability from southwest to northeast gradually increased, sunshine suitability from southeast to northwest gradually increased, and a large spatial distribution of differences in the region’s winter wheat planting planning has brought about a certain degree of difficulty. The south–north gradient of temperature suitability is essentially driven by the latitudinal difference in heat resources: southern areas represented by Xingtai (37.07° N) have an annual accumulated temperature exceeding 4500 °C·d, which fully meets the total heat requirement of winter wheat throughout its life cycle (2000 °C·d, Table 7). In contrast, northern regions such as Zhangbei (41.15° N) suffer from insufficient accumulated temperature, and frequent late frost damage during the rejuvenation stage further reduces temperature suitability. Additionally, the urban heat island effect caused by high urbanization in downtown Beijing leads to a local temperature increase, resulting in a northward bulge of the 0.72 temperature suitability contour. The spatial heterogeneity of precipitation suitability is mainly controlled by topographic and coastal effects: northeastern stations (e.g., Qinglong) are located on the windward slope of the Yanshan Mountains, where orographic lift promotes the formation of clouds and precipitation, resulting in the highest regional precipitation suitability (0.527). In contrast, western plain areas such as Huailai lack topographic forcing for precipitation, and the rain shadow effect leads to low precipitation input, forming a low-suitability trough. The two north–south low-value zones near 117° E (Huailai and Raoyang-Baoding) are also closely related to the rain shadow of the western mountains, which further confirms the dominant role of topography in regulating precipitation distribution. Under the influence of precipitation, it decreases in a stepwise manner from south to north, with higher suitability in the northeastern region. The distribution of propensity rate indicates that the temperature suitability increases in general. Precipitation suitability increased and decreased in half of the regions; the sunshine suitability increases in some regions, but decreases in most. Moreover, the comprehensive climate suitability increases in most regions, but the overall rate is slow, and the distribution shows a radial distribution, with the propensity rate decreasing from the center to the surroundings. The difference in the distribution of accumulated temperature suitability and temperature suitability is evident, which is reflected in the fact that the temperature suitability is higher than accumulated temperature suitability in the southern region, while the accumulated temperature suitability is higher than temperature suitability in the eastern region. Considering the link, the heat conditions around Huanghua and Cangzhou in the southeastern part of the country have a significant advantage over those in the Beijing-Tianjin-Hebei region.

4.3. Comprehensive Evaluation

The above analysis confirms that the current concentration of traditional wheat-growing areas in the Ji’nan region is broadly reasonable; however, the statistical examination of variability (CV) and tendency rates provides a more nuanced interpretation of the climatic parameters. It reveals that while the mean values of temperature and comprehensive climate suitability are encouraging, the high statistical variability in water availability—particularly during critical stages such as between overwintering and rejuvenation—remains the most significant and consistent limiting factor for yield stability. Thus, while maintaining traditional wheat areas, future agricultural planning should not only consider average suitability values, but also prioritize mitigating risks associated with factors that exhibit broad instability, such as precipitation. In this context, it is advisable to gradually expand winter wheat planting north of Langfang, where a significant increase in comprehensive climate suitability is projected, and moderately in the northeastern coastal areas, where precipitation conditions are more suitable and steadily improving—though temperature constraints there may be partially alleviated via targeted film technology [50].

5. Conclusions

This study constructed a climate suitability model for winter wheat in the Beijing-Tianjin-Hebei region of China by calculating the suitability of multiple individual meteorological elements and combining weight and addition methods. It divides the growth period of winter wheat into seven stages, analyzes the variation characteristics of suitability in each growth stage, the temporal and spatial distribution of different suitability, obtains interdecadal changes through tendency rate analysis, and summarizes the spatial distribution and variation characteristics of winter wheat suitability in the region over 50 years.

During each growth stage, the trend of climatic suitability is consistent with the trend of temperature and precipitation, showing a pattern of first decreasing and then increasing, with temperature and precipitation being the key factors. In terms of interannual variation, climatic suitability shows an overall slow growth. In terms of spatial distribution, the climate suitability is generally higher in the south and lower in the north. For the distribution of tendency rates, the comprehensive climate suitability increases in most areas, and most significantly in the central region. The cumulative temperature suitability is significantly different from the distribution of temperature suitability, with a high tendency rate in the northwest and a low one in the southeast.

The research presented a scientific plan for winter wheat planting. It can not only guide the traditional wheat-growing areas in southern Hebei to specifically cope with the temperature and humidity risks during the rejuvenation period and jointing stage but also provide a basis for the planting layout in potential expansion areas such as the north of Langfang and the coastal areas in the northeast, so as to make full use of the climate resources in the entire Beijing-Tianjin-Hebei region and optimize the winter wheat production layout.