北美劳伦大湖遥感表面温度研究

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"北美劳伦大湖表面温度遥感探测" 这篇论文主要探讨了基于遥感技术对北美劳伦大湖表面温度的监测方法。遥感技术在环境科学和气候研究中发挥着至关重要的作用，特别是在理解和应对全球气候变化的影响方面。在本研究中，作者Sitthisak Moukomla和Peter D. Blanken专注于开发一种新的技术，能够通过融合MODIS（Moderate Resolution Imaging Spectroradiometer）陆地表面温度数据（MOD11L2）和MODIS云产品（MOD06L2）来获取所有天气条件下的像素级湖泊表面温度。从2001年7月6日至2014年12月31日，他们收集并分析了总计18,807个场景的数据，其中9373（9434）个场景分别来自MOD11L2和MOD06L2。这项研究的创新之处在于它能够在有云和无云的天气条件下提供连续的湖泊表面温度信息，这对于气候模型的构建和气候变化趋势的分析至关重要。论文的摘要指出，像素级别的GLST（Great Lakes Surface Temperature）与气候变暖和湖泊生态系统的响应紧密相关。通过对这些数据的分析，研究者可以更准确地评估湖泊对气候变化的响应，包括水温变化如何影响冰盖形成、蒸发率、湖流动力学以及生物多样性。这种技术的应用不仅可以提高对湖泊系统状态的实时监控，还可以帮助科学家预测未来气候变化可能带来的影响。此外，结合MODIS数据的云检测和剔除算法，研究者可以克服传统遥感技术在云层遮挡时的观测限制，从而提供更为全面和准确的湖泊表面温度记录。这不仅增强了遥感数据的可用性，也提升了研究的可靠性和精度。这项工作为遥感在环境监测特别是气候变化影响研究中的应用开辟了新的道路。它强调了通过技术创新来克服遥感数据处理中的挑战，并提供了关于如何更有效地利用遥感数据来理解大型水体如北美劳伦大湖的动态和气候变化的实例。这种方法论对于全球其他水体的研究也具有借鉴意义，有助于提升我们对全球气候变化的理解和应对能力。

Remote Sens. 2016, 8, 286 3 of 15

Due to the large spatial extent and the sheer volume of water in the Great Lakes, the lakes have

been shown to play a large role in the surface climate of the region [

]. In the autumn, the heat stored

in the water bodies is released in the form of latent heat of evaporation. Thus, the highest evaporation

rates usually occur during this time of year (late fall and early winter). Shorter day lengths together

with an increase in cloudiness gradually decrease the air temperatures. The temperature of the lakes

continues to decline in the winter, when the frigid and dry Arctic air from the northwest travels over

the moist warmer lakes. In early spring, increasing solar radiation begins to heat the surface and

the overlying atmosphere, resulting in the thaw of snow and lake ice (if any is present). During this

period, the lakes are usually warmer than the land and tend to keep the surrounding area cool, thus

occasionally calm conditions continue well into April. In the summer, the longer sunshine duration

warms the surface layer of water in the lakes, making surface water warmer and less dense than the

heavier and colder water below.

Remote Sens. 2016, 8, 286 3 of 15

Due to the large spatial extent and the sheer volume of water in the Great Lakes, the lakes have

been shown to play a large role in the surface climate of the region [22]. In the autumn, the heat

stored in the water bodies is released in the form of latent heat of evaporation. Thus, the highest

evaporation rates usually occur during this time of year (late fall and early winter). Shorter day

lengths together with an increase in cloudiness gradually decrease the air temperatures. The

temperature of the lakes continues to decline in the winter, when the frigid and dry Arctic air from

the northwest travels over the moist warmer lakes. In early spring, increasing solar radiation begins

to heat the surface and the overlying atmosphere, resulting in the thaw of snow and lake ice (if any is

present). During this period, the lakes are usually warmer than the land and tend to keep the

surrounding area cool, thus occasionally calm conditions continue well into April. In the summer,

the longer sunshine duration warms the surface layer of water in the lakes, making surface water

warmer and less dense than the heavier and colder water below.

Figure 1. The Great Lakes basin boundaries and geographic locations for water surface temperature

measurements.

3. Methods

Wan and Dozier [23] explained a fundamental theory for the land surface temperature (LST)

algorithm based on the Planck function as:

L(λ,T) = ε(λ), B(λ,T

s) (1)

where

L is emitted spectral radiance;

B is brightness temperature;

λ is wavelength;

s is surface temperature (K); and

ε is spectral emissivity Planck function.

However, Equation (1) can only be applied during clear-sky conditions when the spectral

radiance (L) emitted from the surface is detectable. In cloudy conditions, L cannot be retrieved from

Figure 1.

The Great Lakes basin boundaries and geographic locations for water surface

temperature measurements.

3. Methods

Wan and Dozier [

] explained a fundamental theory for the land surface temperature (LST)

algorithm based on the Planck function as:

Lpλ, Tq “ εpλq, Bpλ, T

q (1)

where

L is emitted spectral radiance;

B is brightness temperature;

λ is wavelength;

is surface temperature (K); and

ε is spectral emissivity Planck function.

However, Equation (1) can only be applied during clear-sky conditions when the spectral radiance

(L) emitted from the surface is detectable. In cloudy conditions, L cannot be retrieved from the surface

since the cloud tops, not the surface, is what is detected by the satellites. Therefore, in this study, the

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北美劳伦大湖遥感表面温度研究

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