Welcome back. In the first block, we saw the wind speed instruments for in-situ measurements. In this block, we will focus on remote sensing instruments used for wind measurements starting with the basics. We will first overview the basic concepts of remote sensing applied to the atmosphere. Then we will focus on the physics principle explanation and how we can indirectly obtain measurement of wind speed at different altitudes. Revisiting vector decomposition, basic kinematic concepts, and the Doppler Effect for the case of SODAR and LIDAR instruments. Finally, we'll analyze some case studies to illustrate instrument limitations and how to overcome them. The goal of the remote sensing instruments we will present is to obtain measurements of wind speed at different altitudes in the atmospheric column. The basic principle when using remote sensing is the interaction between the instrument and the environment. An active remote sensing instrument emits a wave with well-known characteristics into the atmosphere. These waves can be electromagnetic, such as radio waves or light waves, or acoustic, such as sound waves. The instrument transducers a microphone or a detector, measures the signal that returns back to the instrument after interacting with the atmosphere. The return signal is different from the emitted signal. As the targets are moving and sending back the signal to the instrument, they become the signal source. When the signal reaches the instrument, its wavelength can be shifted by the Doppler Effect. The frequency shift is governed by the Doppler equation shown here on the screen. It's magnitude can be changed due to attenuation along the path between the instrument and the target of study in the atmosphere. This is partly due to atmospheric gas absorption, molecular scattering of the signal in every direction, and absorption along the path back to the instrument. The result is a weaker signal received at the transducers compared to the emitted signal emitted by the instrument. Analyzing these changes and relating them to the theoretical causes, we can infer valuable information about the environment. Target interacting with radar signal or wind lidar signal can be either liquid hydrometeors, such as rain droplets, or solid hydrometeors such as ice crystals or even snowflakes. Targets can also be smaller particles such as aerosols of different origins. Natural causes as volcanic ashes, desert dust or sea salt, or anthropogenic as sulfates, carbon particles, or soot. For SODARS or wind profiling radars targets are inhomogeneities in the thermal structure of the atmosphere caused by turbulence. After this short overview of remote-sensing basics. Let's first have a closer look to the SODARS. SODAR stands for sound detecting and ranging. Inside this device there is a SODAR. A SODAR is considered of transducers that emit frequencies towards the atmosphere in an audible range. These sound waves that you may hear behind me are emitted in frequencies ranging from 1,000 to 4,000 hertz and the emitted power is a few 100 watts. Now, how does a SODAR work? As for other remote sensing instruments, the measurement principle of a SODAR is based on the Doppler Effect. The Doppler Effect is the physics explanation to the difference in sound pitch we hear when a siren from an ambulance, for example, is moving towards us or driving away from us. SODAR transducers emit pressure waves, impulses at audible frequencies towards the atmosphere. The signal velocity will then be the sound propagation speed. The targets detected by our instrument are moving with the wind. When the emitted signal encounters a target, the signal can be redirected by the physical process called scattering. According to the equations of the Doppler Effect, when the target, which scatters the emitted signal is moving towards the instrument, the scattered signal wavelength becomes shorter. Hence, the scattered signal has a higher frequency. Though, when the target moves away from the instrument, the effect is the opposite. The scattered signal wavelength becomes longer and the scattered signal has a lower frequency. Let's see now what are the targets interacting with the sodar signal. As wind flows in the atmosphere, friction between the atmospheric layers causes inhomogeneities in temperature. This phenomenon is known as turbulence. These inhomogeneities while transported by the wind, are actually capable of reflecting the sound waves emitted by the sodar. The typical size of inhomogeneities detected by the sodars is about 10 centimeters. When the signal comes back to the antenna, the small frequency differences between the emitted and reflected sound waves are analyzed and the wind speed can be deduced using the Doppler equations. This becomes even more interesting if we can somehow determine the altitude at which the signal has been reflected to derive the altitude at which the wind is measured. To determine the altitude, we need to measure the time taken by an emitted sound wave pulse from the emission point, to the location of the target, and back to the antenna. In this case, the targets are temperature inhomogeneities. Knowing the sound propagation speed and using the kinematics equations for a constant velocity movement, we can determine the altitude of the temperature inhomogeneities, and hence the altitude at which wind speed is measured. This means sodar can measure wind speed at multiple altitudes in the atmospheric column. The heart of a sodar is its antenna. It consists of dozens of sonic transducers, combination of speakers, and microphones. Sodar emits sound waves at several different frequencies in 3-5 different directions, in order to accurately quantify the wind speed profile. It detects Doppler shifts in each direction in order to get the most complete view of the wind profile as possible. Due to the attenuation characteristics of the atmosphere, higher power, lower frequency sodars will generally produce greater altitude coverage. For each beam, a value of the wind speed in the beam direction is obtained. Decomposing it in vertical and horizontal wind, where the horizontal components are U in the East-West direction and V in the North-South one. Averaging the horizontal components, we obtain the two horizontal components. As for the vertical component W, the vertical beam gives it directly. The average estimation of the vertical velocity is not necessary in the sodar case. The vertical wind speed is directly measured from the vertical beam and the other two or four beams provide the horizontal components. We will see now some important sodar features. The measurement repetition frequency is one hertz, meaning that a signal is emitted and received every second. The measurement accuracy is on the order of 50 centimeters per second and the mean wind speed profile are obtained by averaging wind speed components during 10 minutes. Altitude resolution is five meters, meaning we can obtain a measurement every five meters. Measurement limitations come from high noise in the measurement environment, rain, and strong wind. In the last part of the block after LiDAR technology, we will come back to the instrument limitations and how we can see it in the data visualization. Another important remote-sensing instruments for wind measurement are LiDARs. As sodars, they also provide wind profiles in the atmospheric column. It is now commonly used for wind power assessment studies. As sodars, the measurement principle of a wind LiDAR relies on the Doppler effect. LiDAR stands for light detecting and ranging, so you can deduce easily that the signal emitted by a LiDAR belongs to the spectrum of electromagnetic waves known as light. Here, the emitted signal is light from the infrared spectral band. We will start with the targets aimed by the wind LiDAR. In the case of a wind LiDAR, the targets are aerosols, very small particles of about one micrometer suspended in the air and moving with the wind. For wind LiDARs, the return signal is due to aerosol backscatter. Slight spectral frequency changes due to Doppler effect are measured in the backscattered signal and compared to the emitted signal. The transmission time between the emission and detection of the backscatter signal give us the altitude of the scattering aerosol, and hence the altitude at which the wind is measured. In the wind LIDAR case, four beams are used to accurately sample the wind profile. From the Doppler effect equations, radial wind is calculated in each beam direction, and their decomposition in horizontal and vertical component is done using the same principle as in the SODAR measurements. As no vertical beam is emitted, the vertical velocity, w, is deduced by averaging the vertical component of the slanted beams. The vertical resolution in LIDAR instrument ranges from 20-50 meters depending on the device. As the illustration in the figure shows, this will give us trustable velocity measurement for height differences at the resolution of the instrument. The time resolution is typically one second. Again, the mean wind profiles can be obtained by averaging wind speeds component over 10-minute periods. The measurement frequency as in the SODAR is one hertz and the accuracy is on the order of 50 centimeters per second. Wind LIDARs rely on the presence of aerosols in the atmosphere to measure the wind velocity. This is indeed a limitation for the instrument. On the other hand, in presence of fog, the LIDAR signal will be strongly attenuated and the scope will be significantly reduced. As mentioned earlier, instrument technology and instrument design are key aspects driving measurement characteristics, such as resolution, accuracy, and precision, but also instrument range, meaning the distance that can be observed with the instruments. Knowing these characteristics allow us to determine measurement limitations and uncertainties, and because different instruments will have different characteristics, the use of different instruments could be necessary to cover different measurement ranges, for example. As an example, let's compare wind LIDAR and SODAR measurements in three distinct situations: in fog, rain, and strong wind. As seen in the figure on the left, in fog condition, the vertical range of wind LIDAR measurements is very limited to less than 100 meters because of strong attenuation of the LIDAR signal by fog droplets. SODAR measurements, however, are mostly unaffected. Wind LIDAR measurements are not affected by strong wind conditions. In the image at the top, we see that the SODAR measurements are significantly affected, showing lower values than the LIDAR or even missing data. In rainy conditions, the wind LIDAR measurements are mostly unaffected while the SODAR don't register any measurements. On these figures, you can see daily averaged wind speed profile derived from LIDAR in light blue and SODAR in red, for three different days. The vertical range of this wind LIDAR is from 40-300 meters above ground, while the range of the SODAR is from 10-200 meters. Their resolution is also different 20 meter for this LIDAR against five meters for the SODAR. Remember that when comparing data between different instruments, resolutions, accuracies, precisions can be quite different. Here, we can combine different instruments to cover a larger measurement range and also more meteorological conditions. The figure on the left shows a comparison of cup anemometer data, wind LIDAR data at 80 meters above the ground. The figure on the right shows that we can reproduce the theoretical logarithmic wind speed profile by combining three types of instruments. In this last slide, we summarize some of the most common information needed when working with different instruments. The table includes all wind measuring instruments that can be found at the Seattle observatory, presenting their spatial and temporal resolution and other information of interest. I thank you for your attention and I hope you are enjoying this MOOC.
